CN114862299B

CN114862299B - Transportation route planning method and device

Info

Publication number: CN114862299B
Application number: CN202210332838.5A
Authority: CN
Inventors: 李超贤; 王轶轩; 王中强; 章鹏; 房磊; 张军
Original assignee: Hema China Co Ltd
Current assignee: Hema China Co Ltd
Priority date: 2022-03-31
Filing date: 2022-03-31
Publication date: 2025-02-18
Anticipated expiration: 2042-03-31
Also published as: CN114862299A

Abstract

The embodiments of this specification provide a method and device for transport route planning, wherein the method comprises: receiving a transport task of a target object within a target time period, wherein the transport task comprises the destination time-space information of each cargo to be transported; obtaining historical transport data according to the destination time-space information of each cargo to be transported, and counting the cargo transport volume of each destination station; determining the transport route of the target object within the target time period according to the historical transport data and the cargo transport volume of each destination station. This method can improve the efficiency and accuracy of transport route planning.

Description

Transportation route planning method and device

Technical Field

The embodiment of the specification relates to the technical field of computers, in particular to a transportation route planning method.

Background

With the development of market economy and the improvement of the logistics specialization level, the transportation task is rapidly developed. In order to improve the transportation efficiency, the transportation task is ensured to be relatively balanced in cost and time, and vehicle scheduling is required.

In the prior art, the transportation route is planned mainly by manpower, but the method has low intelligent level, and the problems of unreasonable transportation route arrangement and serious transportation resource waste exist. Therefore, an effective solution is needed to solve the above-mentioned problems.

Disclosure of Invention

In view of this, the present embodiments provide a transportation route planning method. One or more embodiments of the present specification also relate to a transportation route planning apparatus, a computing device, a computer-readable storage medium, and a computer program that solve the technical drawbacks of the prior art.

According to a first aspect of embodiments of the present specification, there is provided a transportation route planning method, comprising:

Receiving a transportation task of a target object in a target time period, wherein the transportation task comprises destination space-time information of goods to be transported;

according to the destination space-time information of each cargo to be transported, historical transportation data are obtained, and cargo transportation quantity of each destination site is counted;

And determining the transportation route of the target object in the target time period according to the historical transportation data and the cargo transportation quantity of each destination site.

According to a second aspect of embodiments of the present specification, there is provided a transportation route planning apparatus comprising:

the receiving module is configured to receive a transportation task of a target object in a target time period, wherein the transportation task comprises destination space-time information of each goods to be transported;

The statistics module is configured to acquire historical transportation data according to the destination space-time information of each cargo to be transported and to count cargo transportation quantity of each destination site;

And the determining module is configured to determine the transportation route of the target object in the target time period according to the historical transportation data and the cargo transportation quantity of each destination site.

According to a third aspect of embodiments of the present specification, there is provided a computing device comprising:

A memory and a processor;

the memory is configured to store computer-executable instructions that, when executed by the processor, perform the steps of the haul route planning method described above.

According to a fourth aspect of embodiments of the present description, there is provided a computer readable storage medium storing computer executable instructions which, when executed by a processor, implement the steps of the above-described transportation route planning method.

According to a fifth aspect of embodiments of the present specification, there is provided a computer program, wherein the computer program, when executed in a computer, causes the computer to perform the steps of the above-described transportation route planning method.

The transportation route planning method provided by the specification receives a transportation task of a target object in a target time period, wherein the transportation task comprises destination space-time information of goods to be transported, obtains historical transportation data according to the destination space-time information of the goods to be transported, counts the goods transportation quantity of each destination site, and determines a transportation route of the target object in the target time period according to the historical transportation data and the goods transportation quantity of each destination site. The historical transportation data and the cargo transportation amount of each destination site are used for determining the target transportation route corresponding to the target object in the target time period, so that the difference caused by manual wire arrangement is avoided, the efficiency and the accuracy of transportation route planning can be effectively improved, and the transportation route can be accurately determined through the historical transportation data.

Drawings

FIG. 1 is a flow chart of a method of route planning provided in one embodiment of the present disclosure;

FIG. 2A is a schematic diagram illustrating a process of a transport route planning platform in a transport route planning method according to an embodiment of the present disclosure;

FIG. 2B is a process schematic diagram of another method of route planning according to one embodiment of the present disclosure;

FIG. 2C is a schematic diagram illustrating the effect of a method for route planning according to one embodiment of the present disclosure;

FIG. 2D is a schematic diagram illustrating a process of a transport route planning platform according to another method of transport route planning according to one embodiment of the present disclosure;

FIG. 2E is a diagram showing a comparison of a route to a route in a route planning method according to one embodiment of the present disclosure;

FIG. 3 is a process flow diagram of a method of transportation route planning provided in one embodiment of the present disclosure;

FIG. 4 is a schematic diagram of a transportation route planning device according to one embodiment of the present disclosure;

FIG. 5 is a block diagram of a computing device provided in one embodiment of the present description.

Detailed Description

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present description. This description may be embodied in many other forms than described herein and similarly generalized by those skilled in the art to whom this disclosure pertains without departing from the spirit of the disclosure and, therefore, this disclosure is not limited by the specific implementations disclosed below.

The terminology used in the one or more embodiments of the specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of the specification. As used in this specification, one or more embodiments and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used in one or more embodiments of the present specification refers to and encompasses any or all possible combinations of one or more of the associated listed items.

It should be understood that, although the terms first, second, etc. may be used in one or more embodiments of this specification to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first may also be referred to as a second, and similarly, a second may also be referred to as a first, without departing from the scope of one or more embodiments of the present description. The term "if" as used herein may be interpreted as "at..once" or "when..once" or "in response to a determination", depending on the context.

First, terms related to one or more embodiments of the present specification will be explained.

The stations, namely the logistics stations, mainly comprise a processing center, a store, a distribution station and a bin, wherein the bins from the processing center to the fresh processing center can be B2C (Bus iness-to-Consumer) bins, normal temperature bins, cold chain bins and the like.

Intelligent dispatching-traditional dispatching refers to manually arranging the sequence of stations driven by drivers according to experience. Intelligent scheduling refers to the steps of calling an algorithm according to different parameters and outputting a better solution.

The present description will then provide a brief description of a transportation route planning method.

With the development of market economy and the improvement of the logistics specialization level, the transportation task is rapidly developed. In order to improve the transportation efficiency, the transportation task is ensured to be relatively balanced in cost and time, and vehicle scheduling is required. Namely truck dispatching, is used for helping a dispatcher to plan and dispatch a transportation task, and ensures that transportation is relatively balanced in cost and timeliness. When a scheduler generates a scheduling plan, priority of timeliness and cost needs to be fully considered in the project scene. In some scenarios, such as B2C or NB (self-service) links, it is desirable to prioritize shipping timeliness and to secure delivery prior to the time of customer pick-up. The B2B (Business-to-Business) link does not have a great requirement on aging, and only needs to be delivered in a fixed time period, and in this case, transport cost is preferably considered, and transport loading rate needs to be improved.

In the prior art, the transportation route is planned manually, such as by using a manual dispatching mode, the wiring is directly carried out, and for example, a positioner is installed for a vehicle, real-time in-transit information of the vehicle, vehicle driver information and the like are obtained by calling an interface of a positioner provider in real time, the obtained information is displayed on a map, meanwhile, decoupling of a third-party map provider can be called, the current speed information of the vehicle and the like are obtained, and the information is displayed on the map, so that the visual monitoring of the vehicle for the transportation vehicle is realized.

However, when a large number of transportation demands are needed to be met, a large amount of manpower is required for manual spot stringing, after the number of spots reaches a certain level, the manual task cannot be completed, for example, in store transportation, the number of stations in one city is not more than 50, the number of stations is small and fixed, the amount of goods is stable, the line can be manually arranged according to experience to obtain a better solution, but in a self-lifting status, the number of stations required to be distributed in one warehouse reaches hundreds of thousands, the number of stations required to be distributed is not fixed each time, the amount of goods is unstable, the manual task cannot be completed, in addition, the method has low intelligence level, too much dependence on the experience of a scheduler, the difference between the time-keeping and cost-keeping of an excellent scheduler and a general scheduler is large, for example, the manual line-arranging cannot drop the scheduling experience on a system, the off-time rate and the cost-keeping of the scheduler are uncontrollable, and the excellent scheduler can estimate how many vehicles are required to be transported to a plurality of stations when the amount of goods is seen, and the general scheduler cannot estimate how much time is required. Namely, the problems of unreasonable transportation route arrangement and serious transportation capacity resource waste exist.

The method for planning the transportation route comprises the steps of receiving a transportation task of a target object in a target time period, obtaining historical transportation data according to the destination time-space information of the goods to be transported, counting the transportation quantity of the goods at each destination site, and determining the transportation route of the target object in the target time period according to the historical transportation data and the transportation quantity of the goods at each destination site. The historical transportation data and the cargo transportation amount of each destination site are used for determining the target transportation route corresponding to the target object in the target time period, so that the difference caused by manual wire arrangement is avoided, the efficiency and the accuracy of transportation route planning can be effectively improved, and the target transportation route can be accurately determined through the historical transportation data.

In the present specification, a transportation route planning method is provided, and the present specification relates to a transportation route planning apparatus, a computing device, and a computer-readable storage medium, which are described in detail in the following embodiments one by one.

Referring to fig. 1, fig. 1 shows a flowchart of a method for planning a transportation route according to an embodiment of the present disclosure, which specifically includes the following steps.

And 102, receiving a transportation task of the target object in a target time period, wherein the transportation task comprises the destination space-time information of each cargo to be transported.

The execution subject implementing the transportation route planning method may be a computing device having a transportation route planning function, such as a server, a terminal, or the like having a transportation route planning function.

Specifically, the target object refers to a matter for transporting goods, which may be a transportation person, a transportation vehicle, a cargo plane, or the like, and the specification is not limited to this, the target time period refers to a pre-designated time period, such as a future day, a future week, or the like, the transportation task refers to a task generated by purchasing or reserving goods, or returning goods, or the like, when a user or company or organization needs the goods, and the user needs to distribute the goods, for example, the user purchases clothes through a shopping platform, and further, for example, the user distributes files through a running platform, and the target space-time information refers to at least one of a transportation start point, a transportation end point, a predicted arrival time (arrival time), a predicted sending time, a site identifier, or the like, which corresponds to the transportation task.

In practical applications, there are various ways of receiving the transport task of the target object in the target time period, for example, the method may be that an operator sends a command for planning a transport route to an execution subject, or sends a command for receiving the transport task of the target object in the target time period, and correspondingly, the execution subject starts to perform the transport task of the target object in the target time period after receiving the command, or the server automatically obtains the transport task of the target object in the target time period every preset time period, for example, after the preset time period, the server with the transport route planning function automatically obtains the transport task of the target object in the designated access area in the target time period, or the terminal with the transport route planning function automatically obtains the transport task of the target object stored locally in the target time period after the preset time period. The manner in which the transport task of the target object within the target period is received is not limited in this specification.

It should be noted that, the transportation task includes the destination space-time information of each cargo to be transported, for example, the transportation task includes 2 pairs of trousers and 3 pairs of socks, and the destination space-time information of 2 pairs of trousers and 3 pairs of socks is sent from the A place to the B place on day 13 of 3 months.

And 104, acquiring historical transportation data according to the destination space-time information of the goods to be transported, and counting the goods transportation quantity of each destination site.

Specifically, the historical transportation data refers to data corresponding to a target object when the target object executes a previous transportation task, the stations refer to a starting point, a destination point and a transfer station for transporting goods, the destination station refers to a final station to which a certain goods needs to be transported, and the goods transportation quantity refers to the quantity of the goods transported to the destination station.

In practical application, after the transportation task of the target object in the target time period is obtained, further, according to the destination space-time information of each cargo to be transported in the transportation task, historical transportation data related to each destination space-time information is obtained, for example, the delivery date in the destination space-time information is 3 months 15 days, according to the delivery date, historical transportation data of 2 months 15 days is obtained, and if the destination in the destination space-time information is the destination site a, historical transportation data related to the destination site a is obtained. And the cargo transportation amount of each destination site is counted according to the destination space-time information, for example, the destination site to be delivered by each cargo to be transported is determined according to the destination space information of each cargo to be transported in the transportation task, and then the cargo transportation amount of each destination site is determined. The target space information is information representing a space in the target space information.

In one or more optional embodiments of the present disclosure, when acquiring the historical transportation data according to the destination spatial-temporal information of each cargo to be transported, the destination spatial-temporal information may be input into a preset historical transportation data acquiring tool, then the historical transportation data acquiring tool identifies the destination spatial-temporal information to obtain an identifier of the historical transportation data, and then the corresponding historical transportation data is acquired from a preset historical transportation database according to the identifier. In this way, the efficiency of historical transportation data acquisition can be improved.

In one or more alternative embodiments of the present disclosure, when the historical transportation data is obtained according to the destination spatial information of each cargo to be transported, the historical transportation data may also be obtained according to the destination spatial information in the destination spatial information of each cargo to be transported. That is, when the destination space-time information includes the destination site identifier, the historical transportation data is obtained according to the destination space-time information of each cargo to be transported, and the specific implementation process may be as follows:

determining destination sites of the goods to be transported according to the destination site identifiers of the goods to be transported;

and acquiring historical transportation data corresponding to the destination sites of the goods to be transported.

The destination site identifier is information indicating the destination site in the destination space information, may be a name of the destination site, may be a geographical location of the destination site, or may be a reference number of the destination site, which is not limited in this specification.

In practical application, according to destination site identifiers in destination space-time information of goods to be transported, destination sites pointed by the destination site identifiers are determined, namely destination sites of the goods to be transported are determined, and historical transportation data related to the destination sites are obtained according to the destination sites. Thus, the accuracy of the historical transportation data acquisition can be improved.

In one or more alternative embodiments of the present disclosure, the destination spatiotemporal information includes destination site identifiers, at which point cargo traffic for each destination site may be counted based on the destination site identifiers in each destination spatiotemporal information. That is, when the destination space-time information includes destination site identifiers, the cargo traffic of each destination site is counted according to each destination space-time information, and the specific implementation process may be as follows:

And determining the destination space-time information quantity of the destination site identification and representing the destination site aiming at any destination site, and determining the destination information quantity as the cargo traffic of the destination site.

Specifically, the destination site identifier may be a name of the destination site, a geographical location of the destination site, or a label of the destination site, which is not limited in this specification, and the amount of destination spatio-temporal information refers to the amount of destination spatio-temporal information including a certain destination site identifier.

In practical application, comparing destination site identifiers in destination space-time information of goods to be transported with destination sites to determine the goods transportation quantity of the destination sites, wherein for a certain destination site, the destination site identifiers of the destination space-time information are compared with the destination site, if the destination site identifiers of the destination space-time information characterize the destination site, the number of the destination space-time information is increased by one, the goods to be transported corresponding to the destination space-time information is indicated to be transported to the destination site, the goods transportation quantity of the destination site is increased by one, the destination space-time information is traversed, and then the goods transportation quantity of the destination site is determined. Therefore, the number of the destination space-time information is determined only through the destination site identification of the destination space-time information, and then the cargo transportation amount of each destination site is determined, so that not only is other information in the destination space-time information avoided being processed, the data processing amount can be reduced, the rate of the cargo transportation amount can be improved, and the accuracy rate of the cargo transportation amount can be improved.

For example, there are 2 destination sites, destination site A and destination site B, and 5 destination spatio-temporal information, where the destination site in the first destination spatio-temporal information is identified as a, the destination site in the second destination spatio-temporal information is identified as B, the destination site in the third destination spatio-temporal information is identified as B, the destination site in the fourth destination spatio-temporal information is identified as a, and the destination site in the fifth destination spatio-temporal information is identified as a. Assuming that the destination site identifier a represents the destination site A, and the destination site identifier B represents the destination site B, the destination space-time information quantity of the destination site identifier representing the destination site A is 3, namely the cargo traffic quantity of the destination site A is 3, and the destination space-time information quantity of the destination site identifier representing the destination site B is 2, namely the cargo traffic quantity of the destination site B is 2.

In one or more alternative embodiments of the present disclosure, the shipping tasks may correspond to different shipping types, such as shipping the user's purchased goods for delivery, and shipping the user's purchased goods for return, i.e., the shipping tasks may also include a shipping type identifier, where the destination spatiotemporal information includes destination end point identification or destination start point identification, when the destination site is the destination end point or destination start point of the cargo transportation, the destination end or destination start cargo traffic can be determined based on the amount of time-space information. That is, when the transportation task further includes a transportation type identifier, the destination station identifier includes a destination identifier or a destination start point identifier, and the destination station is a destination or a destination start point of the cargo transportation, the cargo transportation amount of each destination station is counted according to the destination space-time information of each cargo to be transported, and the specific implementation process may be as follows:

Under the condition that the transportation type identifier is a purchase identifier, determining the destination space-time information quantity of a destination end point represented by the destination end point identifier aiming at any destination end point, and determining the destination space-time information quantity as the cargo transportation quantity of the destination end point;

and under the condition that the transportation type identifier is a return identifier, determining the destination space-time information quantity of the destination starting point represented by the destination starting point identifier aiming at any destination starting point, and determining the destination space-time information quantity as the cargo transportation quantity of the destination starting point.

The destination site identification is information for representing destination sites in destination space information, can be the name of the destination site, can be the geographic position of the destination site, can also be the label of the destination site, and is the destination site identification required to be delivered by the purchase, such as the destination site closest to the user address of the purchase of the goods, and the destination starting point identification is the destination site identification required to be delivered by the purchase, such as the destination site closest to the merchant address of the delivery of the goods.

In practical application, if the transportation type identifier is a purchase identifier, the transportation task in the target time period is indicated to be the goods purchased by the delivery user, the destination end identifier of each destination space-time information is compared with the destination end aiming at any destination end, if the destination end identifier of a certain destination space-time information characterizes the destination end, the number of the destination space-time information is increased by one, the goods to be transported corresponding to the destination space-time information is indicated to be transported to the destination end, the goods transport volume of the destination end is increased by one, the destination space-time information is traversed, and then the goods transport volume of the destination end is determined. Similarly, if the transportation type identifier is a return identifier, the transportation task in the target time period is indicated to be for delivering the goods purchased by the user, the destination starting point identifier of each destination time-space information is compared with the destination starting point for any destination starting point, if the destination starting point identifier of a certain destination time-space information characterizes the destination starting point, the number of the destination time-space information is increased by one, the goods to be transported corresponding to the destination time-space information is indicated to be transported to the destination starting point, the goods transport volume of the destination starting point is increased by one, the destination time-space information is traversed, and then the goods transport volume of the destination starting point is determined. Therefore, the destination time-space information quantity is determined only by the destination end point identification or the destination starting point identification of the destination time-space information, and then the cargo transportation quantity of each destination end point or destination starting point is determined, so that other information in the destination time-space information is avoided being processed, the data processing quantity can be reduced, the rate of the cargo transportation quantity can be improved, and the accuracy of the cargo transportation quantity can be improved.

And 106, determining the transportation route of the target object in the target time period according to the historical transportation data and the cargo transportation quantity of each destination site.

Specifically, the transportation route refers to a route of transporting goods to be transported by the finally determined target object.

In practical application, after the historical transportation data is obtained and the cargo transportation amount of each destination site is counted according to the space-time information of each destination, further, data analysis and intelligent wire arrangement are needed to be performed based on the historical transportation data and the cargo transportation amount of each destination site, so that a route, namely a transportation route, required by a target object to complete a transportation task in a target time period is determined.

In one or more optional embodiments of the present disclosure, the historical transportation data includes a historical time duration of each destination station and a historical resource consumption amount between each destination station, and the destination space-time information further includes a destination arrival time, where the consumption of each link in the transportation process may be based on the historical time duration of each destination station, the historical resource consumption amount between each destination station, and the cargo transportation amount, and further, the wire arrangement may be performed to determine the transportation route based on the consumption and the destination arrival time. That is, in the case where the historical transportation data includes a historical arrival time of each destination station and a historical resource consumption amount between each destination station, and the destination time-space information further includes a destination arrival time, the determining a transportation route of the target object within the target time period according to the historical transportation data and the cargo transportation amount of each destination station may be performed as follows:

predicting the consumption time of each destination station in the target time period according to the historical station-in time of each destination station and the cargo transportation quantity of each destination station;

predicting and obtaining the inter-station resource consumption of each destination station in the target time period according to the historical resource consumption of each destination station;

and determining the transportation route of the target object in the target time period according to the destination arrival time, the in-station consumption time and the inter-station resource consumption.

Specifically, the historical on-site time length refers to the time length for transporting goods into and out of a certain destination site before the target object, and the historical resource consumption amount refers to the resource value consumed by transporting goods between two destination sites before the target object.

In practical application, for any destination site, the time spent in the destination site in the target time period of the transportation task can be predicted according to the historical time spent in the destination site and the cargo transportation amount, such as 10 minutes, half hours and the like. And traversing each destination station, and predicting the time length of the transportation task required to be consumed at each destination station in the target time period, namely predicting the time length of the transportation task consumed at each destination station in the target time period. And then predicting the inter-station resource consumption of the transport task in the target time period according to the historical resource consumption of all the destination stations corresponding to the transport task. Further, data analysis is performed to line based on destination arrival time, in-station consumption time and inter-station resource consumption, and then a transportation route of the target object in the target time period is determined. Therefore, the in-station consumption time and the inter-station resource consumption of each destination station in the target time period are predicted, and then the wire arrangement is performed based on the destination arrival time, the in-station consumption time and the inter-station resource consumption, so that the transport route of the target object in the target time period is determined, the wire arrangement efficiency can be effectively improved, and the transport route is more accurate.

The historical transportation data includes a historical time length of each destination station and a historical resource consumption amount between destination stations, and at this time, the historical time length of each destination station and the historical resource consumption amount between destination stations need to be obtained. That is, in the case where the historical transportation data includes the historical station duration of each destination station and the historical resource consumption amount between each destination station, the obtaining the historical transportation data according to the destination space-time information of each cargo to be transported may be implemented as follows:

And acquiring the historical on-site time of each destination site, and acquiring the historical resource consumption of the target object among the destination sites.

In practical application, the historical on-station time length corresponding to each destination station can be obtained from the historical on-station time length library, the historical resource consumption between each destination station pair can be obtained from the historical resource consumption library, the travel data of goods transported at each destination station before the destination object is obtained according to the destination station, and then the historical on-station time length of the destination station and the historical resource consumption of the destination object between the destination stations are calculated according to the formation data. Therefore, the historical station duration of each destination station and the historical resource consumption among the destination stations are obtained to represent the historical transportation data, so that the historical transportation data has smaller granularity, the target transportation route determined based on the historical transportation data is more accurate, the cargo transportation is more efficient, the use experience of a user is further improved, and the viscosity of the user is improved.

Further, the consumed resources may be time, cost, time and cost. The historical resource consumption comprises historical inter-station consumption time and/or historical inter-station cost consumption, and when the historical resource consumption of the target object between the destination stations is acquired, the historical inter-station consumption time and/or the historical inter-station cost consumption of the target object between the destination stations are required to be acquired. The historical inter-station consumption time length refers to the time length consumed by the target object between two destination stations, and the historical inter-station cost consumption amount refers to the cost consumed by the target object between two destination stations. The historical inter-station consumption duration and/or the historical inter-station cost consumption between the destination stations are/is obtained to represent the historical resource consumption, the historical transportation data are further refined, namely, even if the granularity of the historical transportation data is smaller, the target transportation route determined based on the historical transportation data is more accurate, the goods transportation is more efficient, the use experience of a user is further improved, and the user viscosity is improved.

In one or more optional embodiments of the present disclosure, the historical on-site duration includes a historical on-site time and a historical off-site time, where the historical processing duration of the destination site for processing the unit cargo may be determined based on the historical on-site time, the historical off-site time, and the historical cargo traffic in the historical transportation data, and the on-site consumption duration of the destination site is further determined based on the historical processing duration of the unit cargo and the current cargo traffic. That is, when the historical on-station duration includes a historical on-station time and a historical off-station time, and the historical transportation data further includes a historical cargo traffic of each destination station, the duration of the consumption of each destination station in the station within the target time period is predicted according to the historical on-station duration of each destination station and the cargo traffic of each destination station, and the specific implementation process may be as follows:

Predicting and obtaining the historical processing time of unit cargoes in a first destination site according to the historical arrival time, the historical arrival time and the historical cargo transportation quantity of the first destination site, wherein the first destination site is any destination site;

And predicting the consumption time of the first destination site in the target time period according to the historical processing time of the unit cargoes in the first destination site and the cargo transportation quantity.

The historical arrival time refers to the time when a target object or other objects enter a certain destination site in a certain historical transportation task, the historical arrival time refers to the time when the target object or other objects exit the certain destination site in a certain historical transportation task, the historical cargo transportation amount refers to the historical arrival time and the historical arrival time period, and the number of cargoes loaded and unloaded at the destination site;

In practical application, for any destination site, according to the historical arrival time and the historical arrival time of the destination site, the historical time consumption at the destination site, namely the historical arrival time, is determined, then according to the historical arrival time and the historical cargo transportation amount of the destination site, the historical processing time of unit cargo in the destination site is calculated, and the calculation process is shown in formula 1. Further, according to the historical processing time length of the unit cargoes in the destination site and the cargo transportation quantity, the in-site consumption time length of the destination site in the target time period of the transportation task is predicted, and the calculation process is shown in the formula 2. Therefore, the time consumption in the station can be more accurately determined, and the accuracy of route planning is improved.

Historical processing duration of unit load = historical on-station duration/historical load of load

Time spent in station = (historic outbound time-historic inbound time)/historic cargo traffic (formula 1) = historic processing time of unit cargo × cargo traffic (formula 2)

For example, the historical outbound time and the historical inbound time of the destination site A are respectively 10:00 and 9:00, and the historical cargo traffic is 10, so that the historical on-site time of the destination site A is 60 minutes, and the historical processing time of unit cargoes is 6 minutes. If the cargo traffic of the destination station a is 20, the time spent in the station is 120 minutes.

In one or more alternative embodiments of the present disclosure, the consumption of resources between stations includes the consumption time between stations or the consumption cost between stations, where the consumption of resources between stations may be obtained according to different requirements, such as time-efficient priority or cost priority, and the destination-to-station time and the consumption time in stations are combined to determine the transportation route of the transportation task. That is, in the case that the inter-station resource consumption amount includes an inter-station consumption time period or an inter-station cost consumption amount, the determining, according to the destination arrival time, the intra-station consumption time period, and the inter-station resource consumption amount, the transportation route of the target object in the target time period may be implemented as follows:

receiving a selection instruction of a user for a route planning mode sent by a client;

Under the condition that the selection instruction carries an aging identifier, determining a transportation route of the target object in the target time period according to the destination arrival time, the in-station consumption time and the inter-station consumption time;

And under the condition that the selection instruction carries a cost identifier, determining a transportation route of the target object in the target time period according to the destination arrival time, the in-station consumption time and the inter-station cost consumption.

The route planning mode is specifically a demand of route planning, such as time-lapse priority or cost priority, the selection instruction is an instruction triggered by the user selecting the route planning mode, the time-lapse identification is an identification corresponding to the route planning mode with time-lapse priority selected by the user, the cost identification is an identification corresponding to the route planning mode with cost priority selected by the user, the inter-station consumption time length is a time length consumed between two destination stations, and the inter-station cost consumption amount is a cost amount consumed between two destination stations.

In practical application, a user can select the needed route planning mode through a client, if the user selects the route planning mode with priority for timeliness, the locally received selection instruction carries timeliness identification, at this time, route planning is needed to be carried out based on destination arrival time, in-station consumption time and inter-station consumption time, and a transportation route of a target object in a target time period with priority for timeliness is determined, if the user selects the route planning mode with priority for cost, the locally received selection instruction carries cost identification, at this time, route planning is needed to be carried out based on destination arrival time, in-station consumption time and inter-station cost consumption, and the transportation route of the target object in the target time period with priority for cost is determined. In this way, the transportation route of the object can be provided based on different demands of the customer, and the viscosity of the user is greatly improved.

In one or more alternative embodiments of the present disclosure, before receiving a user selection instruction for a route planning manner sent by a client, a reference needs to be provided to the user to select the route planning manner by the user. That is, before the receiving instruction of the user for selecting the route planning mode sent by the client, the method further includes:

Calculating the total consumption time length corresponding to each transport route to be selected according to the consumption time length in the stations and the consumption time length between the stations;

calculating the total cost consumption corresponding to each transport route to be selected according to the inter-station cost consumption;

And sending the total consumption time and the total cost consumption corresponding to the transport routes to be selected to a client for display so that a user can select a route planning mode according to the total consumption time and the total cost consumption corresponding to the transport routes to be selected.

The method comprises the steps of selecting a transport route to be selected, wherein the transport route to be selected is a plurality of initial routes obtained through preliminary wire arrangement of each destination site, the total consumed time is the total time required by a target object to complete transport tasks in a target time period through a certain selected transport route, and the total cost consumption is the cost required by the target object to complete transport tasks in the target time period through a certain selected transport route.

In practical application, a preliminary route planning can be performed based on destination sites of goods to be transported to obtain a plurality of transport routes to be selected, then the total consumption time length corresponding to each transport route to be selected is calculated according to the in-site consumption time length of each destination site and the inter-site consumption time length between each destination site, and the total cost consumption corresponding to each transport route to be selected is calculated according to the inter-site cost consumption amount between each destination site. And displaying the total consumption time and the total cost consumption corresponding to each transport route to be selected through the client for the user to check, wherein the user can select a route planning mode according to the total consumption time and the total cost consumption corresponding to each transport route to be selected.

For example, destination stations are three, destination station b1, destination station b2 and destination station b3, wherein destination station b1 is the start station, and assuming that the inter-station time consumption of destination station b1, destination station b2 and destination station b3 is 10 minutes, 20 minutes and 15 minutes, respectively, the total inter-station time consumption between destination station b1 and destination station b2 is 25 minutes, the total inter-station time consumption between destination station b1 and destination station b3 is 10 minutes, the total inter-station time consumption between destination station b2 and destination station b3 is 30 minutes, the inter-station cost consumption of destination station b1 to destination station b2 is 6, the inter-station cost consumption of destination station b1 to destination station b3 is 8, the inter-station cost consumption of destination station b2 to destination station b3 is 9, and the inter-station cost consumption of destination station b3 to destination station b2 is 10. The two transport routes to be selected are determined according to the destination site b1, the destination site b2 and the destination site b3, wherein the transport route 1 to be selected is 'destination site b1, destination site b2 and destination site b 3', the transport route 2 to be selected is 'destination site b1, destination site b3 and destination site b 2', the total consumption time of the transport route 1 to be selected is 10+20+15+25+30=100 minutes, the total cost consumption is 6+9=15, the total consumption time of the transport route 2 to be selected is 10+20+15+10+30=85 minutes, and the total cost consumption is 8+10=18. The total time period of 100 minutes and total cost consumption 15 for the haul route 1 to be selected and the total time period of 85 minutes and total cost consumption 18 for the haul route 2 to be selected are then sent to the client for display.

In one or more optional embodiments of the present disclosure, in a case where the transportation type identifier is a purchase identifier, the cargo conveyance amount to be the destination end point is determined, or in a case where the transportation type identifier is a return identifier, after the cargo conveyance amount to be the destination start point is determined, it is also necessary to determine the transportation route of the target object within the target period based on the cargo conveyance amount to be the destination end point or the cargo conveyance amount to be the destination start point, and the historical transportation data. Namely, according to the historical transportation data and the cargo transportation amount of each destination site, determining the transportation route of the target object in the target time period, wherein the specific implementation process can be as follows:

Under the condition that the transportation type identifier is a purchase identifier, a warehouse site is taken as a starting point, and a transportation route of the target object in the target time period is determined according to the historical transportation data and the cargo transportation quantity of each destination end point;

And under the condition that the transportation type identifier is a return identifier, determining a transportation route of the target object in the target time period by taking a warehouse site as an end point according to the historical transportation data and the cargo transportation quantity of each destination starting point.

In actual application, when the transportation type identifier is a purchase identifier, the initial site, namely the warehouse site, is a departure site of goods, namely a starting point, and at the moment, the warehouse site is used as the starting point, and data analysis and intelligent wire arrangement are performed based on historical transportation data and the goods transportation quantity of each destination end point, so that a route, namely a transportation route, of a target object, which is required to travel when the transportation task is completed in a target time period, is determined, and forward wire arrangement can be realized, and materials are sent to each destination end point from the warehouse site for selling, serving and the like. Under the condition that the transportation type identifier is a return identifier, the initial site, namely the warehouse site, is a delivery site of goods, namely the terminal point, at the moment, the warehouse site is used as the terminal point, and data analysis and intelligent wire arrangement are carried out based on historical transportation data and the goods transportation quantity of each destination starting point, so that the route, namely the transportation route, of a target object required to travel for completing a transportation task in a target time period is determined, and reverse wire arrangement can be realized, and goods and materials from the destination starting point are returned to the warehouse site.

It should be noted that, the user may participate in route planning through the client, such as adding some planning requirements, adjusting the route, and so on. Namely, according to the historical transportation data and the cargo transportation amount of each destination site, determining the transportation route of the target object in the target time period, wherein the specific implementation process can be as follows:

receiving planning additional parameters sent by a client;

and determining the transportation route of the target object in the target time period according to the historical transportation data, the cargo transportation quantity of each destination site and the planning additional parameters.

Specifically, the planning additional parameter refers to a parameter of the route planning provided by the user based on the planning requirement in the route planning.

In practical application, when route planning is performed, a user can input a plurality of planning additional parameters through a client, or input user requirements, the client converts the planning additional parameters according to the user requirements, and then the planning additional parameters are sent to the local. And analyzing and intelligently arranging wires based on historical transportation data, cargo transportation quantity of each destination site and planning additional parameter data locally, so as to determine a route required by the target object to complete the transportation task within the target time period, namely a transportation route. Therefore, the transportation route is determined based on the planning additional parameters, so that the transportation route which meets the requirements of the user can be obtained, namely, the accuracy of the transportation route is improved, the efficiency of cargo transportation is further improved, and the viscosity of the user is improved.

In one or more alternative embodiments of the present disclosure, to improve the efficiency and accuracy of determining a transportation route, a route planning model may be trained in advance, and then a transportation route for a target object within a target time period may be determined based on historical transportation data, cargo traffic for each destination site, and the route planning model. That is, the determining the transportation route of the target object in the target time period according to the historical transportation data and the cargo transportation amount of each destination site may be implemented as follows:

And inputting the historical transportation data and the cargo transportation quantity of each destination site into a pre-trained route planning model to obtain a transportation route of the target object in the target time period, wherein the route planning model is obtained based on sample transportation task training carrying a label route.

The method comprises the steps of determining a model of a road planning, wherein the model of the road planning is a preset neural network model or function, a sample transportation task is a preset transportation task, can be a historical transportation task or a planned transportation task, and a label route is a route with a good transportation effect, such as a transportation route with the shortest transportation time and a transportation route with the least transportation cost, corresponding to the sample transportation task.

In practical application, a route planning model can be trained in advance, namely a sample transportation task carrying a label route is obtained, then a neural network model or function with preset input value of the sample transportation task is output by the neural network model or function, the predicted transportation route of the sample transportation task and the label route carried by the sample transportation task are input into a preset loss function, and the loss value is determined. Further, parameters of the neural network model or the function are adjusted according to the loss value, then a sample transportation task carrying a label route is continuously obtained, the next training is started until the loss value is smaller than a preset threshold value or the iteration number reaches the preset iteration number, the training is stopped, and the trained neural network model or function is determined to be a route planning model.

In addition, after the historical transportation data and the cargo traffic of each destination site are obtained, the historical transportation data and the cargo traffic of each destination site can be sent to a trained route planning model, the route planning model processes the historical transportation data and the cargo traffic of each destination site, and a transportation route of a target object in a target time period is output. Therefore, the historical transportation data and the cargo transportation amount of each destination site are subjected to the route planning model, so that the automatic arrangement of the transportation route is realized, the manpower and material resources are saved, the efficiency and the accuracy of the determined transportation route are improved, and the user can be better served.

In one or more alternative embodiments of the present description, different route planning models are provided for different transportation consumption indicators in order to further improve the accuracy of the transportation route. Namely, before the historical transportation data and the cargo traffic of each destination site are input into a pre-trained route planning model to obtain the transportation route of the target object in the target time period, the specific implementation process may be as follows:

receiving a transportation consumption index, the transportation consumption index comprising a transportation time-consuming index and/or a transportation cost index;

and determining a route planning model corresponding to the transportation consumption index.

The transportation consumption index is a consumption index to be achieved by the pointer for transporting the goods at the time, the transportation time consumption index is a time consumption index to be achieved by the pointer for transporting the goods at the time, and the transportation cost index is a cost consumption index to be achieved by the pointer for transporting the goods at the time.

In practical applications, the display panel may have transportation consumption indicators selected by the user, such as a transportation time-consuming indicator, a transportation cost indicator, and a transportation time-consuming indicator and a transportation cost indicator. The user can select the corresponding transportation consumption index according to the requirement, namely, the transportation consumption index is received, and then the corresponding route planning model is obtained based on the received transportation consumption index.

For example, the transportation consumption index is a transportation time-consuming index, a route planning model for determining a transportation route based on transportation time consumption is obtained, for example, the transportation consumption index is a transportation cost index, a route planning model for determining a transportation route based on transportation cost is obtained, for example, the transportation consumption index is a transportation time-consuming index and a transportation cost index, and for example, a route planning model for determining a transportation route based on transportation time consumption and transportation cost is obtained.

In one or more alternative embodiments of the present description, different route planning models are provided for different transportation scenarios in order to further improve the accuracy of the transportation route. Namely, before the historical transportation data and the cargo traffic of each destination site are input into a pre-trained route planning model to obtain the transportation route of the target object in the target time period, the specific implementation process may be as follows:

acquiring a transportation scene identifier of the target object;

And determining a route planning model corresponding to the transportation scene identification.

Specifically, the transportation scenario identifier refers to a name, a label, etc. corresponding to the transportation scenario.

In practical application, the display panel is provided with a transportation scene identifier for the user to select, such as a vegetable transportation scene identifier, a clothing transportation scene identifier, and a city running leg scene identifier. The user can select the corresponding transportation scene identifier according to the requirement, namely, the transportation scene identifier is acquired, and then the corresponding route planning model is acquired based on the acquired transportation scene identifier. Therefore, different route planning models can be acquired aiming at different transportation scenes, the accuracy of the target transportation route is improved, the efficiency of cargo transportation is improved, and the viscosity of a user is improved.

In one or more alternative embodiments of the present description, a shipping route may be presented to a user from the shipping route after the shipping route is determined, and the user may adjust the shipping route if not satisfied with the shipping route. That is, after determining the transportation route of the target object in the target time period according to the historical transportation data and the cargo transportation amount of each destination site, the method further includes:

The transportation data are sent to a client for display;

And under the condition that a route adjustment instruction aiming at the transportation data is received, adjusting the transportation route according to adjustment parameters carried in the route adjustment instruction to obtain an adjusted transportation route.

The route adjustment instruction is an instruction for adjusting the transportation route sent by a user or the user through a server, and the adjustment parameter is a parameter for adjusting the transportation route so as to improve the transportation route and form the transportation route meeting the requirements of the user.

In practical application, intelligent wire arrangement can be performed according to historical transportation data and cargo transportation amount of each destination site, so that a route required to be traveled by a target object to complete a transportation task in a target time period, namely, a transportation route of the target object in the target time period is determined. And displaying the transportation route to the user through the client, and if a route adjustment instruction for adjusting the transportation route is received, adjusting the transportation route according to adjustment parameters in the route adjustment instruction to obtain an adjusted transportation route.

When a route adjustment instruction is received, the transportation route is adjusted according to an adjustment parameter carried in the route adjustment instruction, and if the route adjustment instruction is received again, the adjusted transportation route needs to be adjusted again. Therefore, through the adjustment of the transportation route, the transportation route which meets the requirements of the user can be obtained, namely, the accuracy of the transportation route is improved, the efficiency of cargo transportation is further improved, and the viscosity of the user is improved.

In addition, after the transportation route is determined, the transportation index corresponding to the transportation route can be determined, and the transportation route and the transportation index are displayed to the user. The method comprises the steps of determining a transport route of a target object in a target time period according to historical transport data and cargo transport volumes of destination sites, calculating transport indexes corresponding to the transport route, and sending the transport route and the transport indexes to a client for display. The transportation index refers to parameter information of a transportation route, such as indexes of time, course, operation duration, loading rate and the like of a certain destination site. Therefore, the user can simply and intuitively check the transportation index of the transportation route, and the degree of association with the user is provided.

Referring to fig. 2A, fig. 2A is a schematic diagram illustrating a processing procedure of a transportation route planning platform in a transportation route planning method according to an embodiment of the present disclosure, where a transportation management system receives an order, that is, a transportation task within a target time period, and the transportation task includes a transportation date, a starting point, and an ending point, that is, destination time-space information, and may further include cargo attribute information, such as weight, quantity, and volume of cargo to be transported. And then importing/synchronizing orders into the visual intelligent flat cable for planning, and setting orders, namely the orders, by the visual intelligent flat cable, wherein the orders comprise delivery date, temperature layer type, task line and the like. Further, all the information is summarized to carry out cargo quantity statistics, namely, the cargo transportation quantity of each destination site is determined according to the destination space-time information, and further, the transportation route is automatically generated based on intelligent wire arrangement according to wire arrangement strategies such as wire arrangement preference (time effect priority and cost priority), vehicle type rules, bill cutting rules and the like, and the transportation route can also be generated based on manual wire arrangement. The transportation route may then be adjusted to generate a bill or to export the transportation route. And further guiding out/synchronizing the transportation route, carrying out vehicle dispatching, then carrying out cargo transportation according to a scheme of vehicle dispatching, and charging while monitoring the cargo transportation process.

In addition, the transportation management system provides the basic capability of constructing the wire arrangement, and can forward wire arrangement (such as delivering materials to a store for selling from a warehouse end), reverse wire arrangement (such as wire arrangement for tasks related to returning goods), pre-wire arrangement (such as predicting transportation routes for several days in the future by predicting the quantity of goods), wire tracking (on the transported routes already arranged, adding stations, adding operation information after part of stations have additional quantity of goods after wire arrangement in advance, adding operation information after warehouse operation is issued), support manual intervention, introduce the manual wire arrangement, copy a certain antenna wire before copying for map page display, acquire path data in advance for determining transportation route calculation, support strategicalization, white box and simulation of the transportation route for trial calculation.

The transportation route planning platform deposits the capability of a wire arrangement algorithm, can predict departure rhythms, delineate on-road navigation time, predict station operation time and delineate vehicle loading, for example, calculates historical average loading time (historical outbound time-historical inbound time) according to the time of a historical vehicle entering and exiting a certain destination station, namely predicts departure rhythms, obtains the average on-road time according to the historical navigation time, obtains information such as a certain transportation vehicle maximum volume as xxx pieces/xxx orders according to the historical navigation time, the historical single piece operation time (historical processing time of unit cargos) and the historical single piece operation time (the historical single piece operation time). Various navigation modes can be deposited for navigation services, such as cost preference and beaten track preference for users to select, namely road network/aging.

The transportation management system can also build wire arrangement strategy capability, such as wire arrangement strategy, precipitate relevant parameters of wire arrangement, carry out standardization for users to use, enable the users to modify the parameters according to requirements and obtain results more suitable for project scenes, and further, for example, index visualization, the wire arrangement results are presented by indexes, and also the logistics network is visualized, so that the indexes such as arrival time, mileage, operation duration, loading rate and the like can be displayed, such as sites (position information, constraint of vehicles, constraint of time windows and containers), routes (distance aging and block division), vehicles (carrying capacity and loading and unloading duration) and capacities are definitely achieved.

The transportation management system is based on a certain platform and mainly comprises a tenant system, an account system, an organization architecture, a permission system and a configuration center. The visual intelligent flat cable can interact with a METIS algorithm (based on a multi-level recursion two-way splitting method, a multi-level K-way splitting method and a multi-constraint splitting mechanism), the visual intelligent flat cable provides rule input for the METIS algorithm platform, and the METIS algorithm platform outputs feedback algorithms such as road network/aging provided by navigation service, rules input by the visual intelligent flat cable, tenant registration, strategy configuration, algorithm output, learning optimization and the like to the visual intelligent flat cable, wherein tenant registration can be provided by the platform base for the METIS algorithm platform, and the logistics network can provide basic data for the METIS algorithm platform to learn optimization.

The transportation route planning provided by one or more embodiments of the present disclosure has two index outputs and two product outputs, wherein the two index outputs are an aging index, a wire-laying down time, a cut-off time, a planned arrival time of each station, a planned departure time of each station, a planned in-place time, an in-transit time and an in-station operation time, and a cost index, a number of series points, a total cargo amount, a total volume, a total weight and a loading rate. The two products are produced by intelligent wire arrangement, replacement of manual wire arrangement, efficiency improvement, data analysis capability, data display of wire arrangement results and optimization of parameter input according to the results. An intelligent wire arrangement algorithm is also deposited, wherein the wire arrangement algorithm is used for discharging a line according to data such as a station, a cargo amount and the like, calling historical data in real time to acquire station operation time and on-road time, and rolling departure vehicles can be started according to shift or interval time. In addition, the method can accurately predict transportation timeliness, accurately feed back outbound time by using historical data, guide drivers and site operation to prepare in advance, follow-up responsibility, analyze management problems and improve efficiency. The method not only establishes a unified wire-arranging data center, namely a large amount of historical operation data, in-station operation time, warehouse-out time and the like, but also deposits related index data of the wire-arranging results, so that the wire-arranging can be analyzed at a glance, and the distributed storage of ADB (analytical database Mysql) is used, thereby supporting full-index query and having super-strong data analysis capability. The new task can be accessed quickly, the new project can be accessed only by importing basic site data, and the bus cable can be produced more accurately by docking and navigation when the historical operation data is increased.

In one or more alternative embodiments of the present description, different route planning methods need to be employed for different transportation tasks of the transportation sign. Namely, before the historical transportation data is obtained according to the destination space-time information of each cargo to be transported, the method further comprises the steps of:

Identifying a transportation identifier of the transportation task;

correspondingly, the obtaining historical transportation data according to the destination space-time information of each cargo to be transported comprises the following steps:

And under the condition that the transportation identifier is a dynamic transportation identifier, acquiring historical transportation data according to the destination space-time information of each cargo to be transported, wherein the dynamic transportation identifier represents that the variation between the transportation task and the historical transportation task is larger than a preset value.

The dynamic transportation identification represents that the variation between the transportation task and the historical transportation task is larger than a preset value, namely, the transportation route is not fixed every day or within a period of time, the variation is larger, such as purchasing of self-lifting class, and the transportation route needs to be recalculated every day according to the order of a client user and the uncertainty of a destination site every day.

In practical application, after a transport task of a target object in a target time period is acquired, a transport identifier of the transport task is identified, if the transport identifier is a dynamic transport identifier, historical transport data are acquired according to destination space-time information of goods to be transported in the transport task, the cargo transport volume of each destination site is counted, and a transport route of the target object in the target time period is further determined according to the historical transport data and the cargo transport volume of each destination site. Therefore, the accuracy of determining the transportation route can be improved by selecting the corresponding route planning method based on the transportation identifier.

In one or more alternative embodiments of the present description, the transportation identifier may be a static transportation identifier, in which case the determination of the transportation route is performed based on the static transportation identifier, that is:

Under the condition that the transportation identifier is a static transportation identifier, a re-carved route is obtained according to the transportation task, wherein the static transportation identifier represents that the variation between the transportation task and the historical transportation task is smaller than or equal to a preset value, and the re-carved route is any historical transportation route;

Determining the similarity between a plurality of historical sites contained in the re-carved route and each destination site;

And determining the transportation route of the target object in the target time period according to the route planning strategy corresponding to the similarity and the re-carved route and each destination site.

Specifically, the dynamic transportation identifier represents that the variation between the transportation task and the historical transportation task is smaller than or equal to a preset value, that is, the change of the transportation route in each day or in a period of time is smaller, such as trunk transportation and point-to-point transportation.

In practical application, after a transport task of a target object in a target time period is acquired, a transport identifier of the transport task is identified, if the transport identifier is a static transport identifier, a historical transport route and/or an alternative transport route is acquired, and then a route is selected from the historical transport route and/or the alternative transport route to be used as a re-carved route. Further, the similarity between the re-route and each destination site is calculated, namely, the similarity between a plurality of historical sites contained in the re-route and each destination site is calculated. And then selecting a route planning strategy corresponding to the similarity, and analyzing the re-carved route and each destination site according to the route planning strategy, namely adjusting the re-carved route based on each destination site to determine the transportation route of the target object in the target time period. Therefore, the transportation route can be determined based on the repeated route, time consumption of route planning in a complex scene can be reduced, more time is striven for warehouse production and subsequent real-time transportation, and meanwhile, cost and threshold of route planning are reduced.

It should be noted that, the resculpting route may be a plurality of historical transportation routes which are screened from the historical transportation route set within a period of time, have the historical goods quantity close to the goods quantity of the transportation task and have higher scores, and the plurality of historical transportation routes are sorted according to the weighted scores, and then one historical transportation route is selected as the resculpting route according to the preset condition or the preset parameter. Or other modes such as flat cable trial calculation and the like are adopted to obtain a satisfactory alternative transportation route, and the alternative transportation route is taken as a re-carved route. And selecting one transportation route from the historical transportation routes and the alternative transportation routes according to preset conditions or preset parameters to serve as a resculpting route.

In one or more alternative embodiments of the present disclosure, the similarity may be greater than a preset similarity threshold, and if the similarity threshold is greater than the preset similarity threshold, the point-to-point accurate matching policy is selected for route planning, and if the similarity threshold is not greater than the preset similarity threshold, the point-to-point accurate matching policy is selected for route planning. That is, the route planning strategy corresponding to the similarity determines, according to the re-route and the destination sites, a transportation route of the target object in the target time period, which may specifically be as follows:

If the similarity is larger than a preset similarity threshold, judging whether the re-carved route comprises the target site or not according to any target site, and determining a transportation route of the target object in the target time period according to a judging result;

If the similarity is smaller than or equal to the similarity threshold, determining a transport plane corresponding to the re-carved route, identifying whether the transport plane contains the destination site for any destination site, and determining the transport route of the target object in the target time period according to the identification result.

In practical application, after calculating the similarity between a plurality of historical sites and each destination site contained in the repeated route, different route planning strategies are selected according to a preset similarity threshold. If the similarity is greater than a preset similarity threshold, a point-to-point accurate matching strategy is used, namely, whether the target station exists in the repeated etching line or not is judged according to any target station, if so, the target station is added to the transportation route, and if not, the target station is not added to the transportation route. And traversing all destination sites to obtain the transportation route of the target object in the target time period. If the similarity is not greater than a preset similarity threshold, a strategy that the facing points contain matching is used, namely, a transport surface corresponding to the re-carved route, namely, a convex hull, is determined firstly, whether the destination site exists in the transport surface is judged according to any destination site, if so, the destination site is added to the transport route, and if not, the destination site is not added to the transport route. And traversing all destination sites to obtain the transportation route of the target object in the target time period. Therefore, the transportation route can be determined based on the repeated route, time consumption of route planning in a complex scene can be reduced, more time is striven for warehouse production and subsequent real-time transportation, and meanwhile, cost and threshold of route planning are reduced.

In addition, for the case that the similarity is not greater than the preset similarity threshold, after the transportation route is determined, for the non-arranged stations, that is, the stations which are not added to the transportation route, the distance from the transportation route is only required to be further judged whether the current stations can be installed after being added to the route and the performance aging can be met if the distance is smaller than the preset accommodation threshold, if the current stations are met, the non-arranged stations are added to the transportation route, and if the current stations cannot be met, the current stations are not added to the transportation route.

Referring to fig. 2B, fig. 2B is a schematic diagram illustrating a processing procedure of another method for planning a transportation route according to an embodiment of the present disclosure, in which a similarity between a route to be re-carved and a destination site is calculated, and then whether the similarity is greater than a similarity threshold is determined.

If so, carrying out point-to-point accurate matching, namely counting a site set in the re-etching route, then carrying out point-to-point accurate matching according to longitude and latitude, namely judging whether each destination site exists in the re-etching route according to the longitude and latitude of each site in the site set, if so, taking the destination site into a transportation route, if not, taking the destination site out of the transportation route, traversing all the destination sites to generate a transportation route, and then outputting the transportation route.

If not, carrying out face-to-point inclusion matching, namely firstly calculating a site convex hull (minimum circumscribed polygon) in a repeated line, namely conveying a face, then carrying out face-to-point inclusion matching according to a graph (convex hull) relation, namely, whether all destination sites are included in the current convex hull or not is matched one by one, if so, the destination sites are included in the conveying line, if not, the conveying line is not included, and all destination sites are traversed to generate the conveying line. In order to further reduce the work of the dispatcher, after the steps are completed, the distance between the non-arranged site and the transportation route can be calculated, whether the distance is larger than the accommodation threshold value is judged, if not, the loading capacity of the transportation route needs to be calculated, the estimated aging is estimated, whether the loading capacity and the aging are met after the non-arranged site is added is further judged, namely, whether the current site can be loaded down after the line is added and the performance aging can be met is judged, if yes, the non-arranged site is added to the transportation route, and if not, the non-arranged site is not added to the transportation route. After traversing all destination sites, outputting a transportation route.

Referring to fig. 2C, fig. 2C shows an effect schematic diagram of a method for planning a transportation route according to an embodiment of the present disclosure, where a re-route includes stations 1-7, and a destination station includes stations 1-5 and 7-10, where a wire arrangement is not required at station 6, and stations 8, 9, and 10 are newly added stations with respect to the re-route. For point-to-point accurate matching, whether the destination stations exist in the re-carved lines or not is compared one by one, if so, the destination stations are included in the corresponding transportation lines, so that the stations 1-6 and 7 are included in the transportation lines, the stations 8-10 are not included in the transportation lines, and a dispatcher can manually adjust the destination stations. The facing points contain matches, compute the convex hull of the rescheduled line (the smallest circumscribing polygon, i.e., the polygon in fig. 3), and compare whether each destination site is contained by the convex hull, if so, is included in the transport route, sites 1-5 and 7-8 are included in the transport route, after which the distance of the undischarged site to the transport route is computed, the distance of the undischarged site 9 to the transport route is less than the accommodation threshold, the distance of the undischarged site 10 to the transport route is greater than the accommodation threshold, the destination site 9 is included in the transport route, and the destination site 10 is not included in the transport route.

Referring to fig. 2D, fig. 2D shows a schematic diagram of a processing procedure of a transportation route planning platform in another transportation route planning method provided in an embodiment of the present disclosure, where the transportation route planning platform includes three units, which are transportation scheduling preparation units for recommending proper high-quality historical transportation routes, a route re-engraving unit for actually performing route re-engraving and completing wire arrangement and scheduling, and a transportation real operation and statistics unit for performing real operation based on the transportation routes and counting real operation results respectively for feeding back next wire arrangement scheduling.

And the transportation scheduling preparation unit is used for receiving the cargo traffic of each destination site through the transportation management system, namely receiving the transportation task, searching for a scheduling result with close cargo traffic and higher scoring from the historical transportation route within a period of time (such as the last 2 months), for example, calculating the first similarity with the historical cargo traffic and scoring the historical scheduling result, and then sequencing according to the weighted scores to recommend a high-quality historical transportation route available for resculpting to a scheduler. The scheduler selects a proper historical transportation route as a re-etching route after comparison, namely the scheduler selects the re-etching route, or the scheduler finds a more satisfactory historical route after re-etching and can also re-initiate the re-etching, besides the historical transportation route, the scheduler can also obtain a satisfactory route planning result through other modes such as wire arrangement trial calculation, namely the route planning result actively selected by the scheduler, and the route re-etching is started after the route planning result is led into the system, namely the scheduler selects the re-etching route.

And the route re-etching unit is responsible for completing the recommendation of re-etching and transportation capacity of the route. There may be a large difference in the number or variation of destination sites in different scenarios. For example, in the scene of buying vegetables on the user line, the destination site has large change, the destination site has small change under the scene of not promoting the destination site greatly, the similarity rate is about 70 percent, and in the scene of buying vegetables on the user line to the store, the destination site has more coverage groups and is self-owned, and the similarity rate is basically 100 percent. Such differences may place different demands on the line review. And if not, if the accurate matching strategy is still adopted, a large number of stations do not have belonging transportation lines, a large amount of time is still required for adjustment by a dispatcher, so that the strategy that the facing points contain matching is used, the higher flexibility is realized, and the work of the dispatcher is reduced. And then outputting the transportation route. After the transportation route is obtained, the dispatching work of the driver and the vehicle is required, the best matching transportation capacity information of each transportation route is obtained after the familiarity of the driver to the site and the familiarity of the driver to the route are obtained, the weighted sum is counted on the transportation route, and then the recommended driver is obtained, and the wire arrangement dispatching result is output. Therefore, after a certain driver runs the same area for a plurality of continuous days, the familiarity of the driver to the area is increased, the driver can continue to serve the area, and the transportation and handover efficiency of the driver is improved.

And the transportation real operation and statistics unit is used for determining and submitting the wire arrangement dispatching result by a dispatcher after the wire arrangement dispatching result. Further entering a transportation actual operation, calculating a dispatching result after the transportation actual operation is finished, calculating familiarity of a driver to a site (for example, the familiarity of the driver to the site is +1 when the driver reaches the site a in actual operation) and familiarity of the driver to a line (the familiarity of the driver to the line is +1 when the driver performs the site a to the site B once in actual operation), and providing a data base in future wire arrangement dispatching. The scheduling result is an examination of the transportation task, and is mainly an aging examination of arrival and departure.

Therefore, the driver familiar with the route and the station is selected to execute the transportation task according to the familiarity, the dependence on the navigation of the driver can be avoided, the navigation cost is reduced, the efficiency of the dispatcher can be improved, the dependence of the warehouse on the full-time dispatcher is reduced, the threshold of the dispatcher is reduced, the dispatcher is helped to iterate the wire arranging result more easily, and the wire arranging dispatching effect is improved. Meanwhile, based on the point-to-point accurate matching or the facing point containing matching, the vehicle effect can be improved on the premise of meeting the aging, the transportation cost is reduced, and the special situations of goods volume fluctuation, site fluctuation and the like are compatible.

Referring to fig. 2E, fig. 2E is a comparison diagram of a re-carved route and a transportation route in a transportation route planning method according to an embodiment of the present disclosure, where the re-carved route is a city a-route 5, a carrier is company B, a driver is a red, a license plate number is 123456, stations are 10, total mileage and forward mileage are 12 km, total goods are 20, a volume is 0.5 cubic meter and a weight is 25 kg, a station distribution sequence is marked in the re-carved route, and the original sequence is preserved in a duplication process. The transportation route is a district A-route 5 of a certain city, wherein the carrier is company B, the driver is Ming, the license plate number is 654321, the stations are 8, the total mileage and the forward mileage are 10 kilometers, the total goods amount is 15 pieces, the volume is 0.4 cubic meter and the weight is 20 kg, and the order of the station delivery is marked in the transportation route.

In addition, the transportation route is determined through the route planning model, the cost and the time effect can be simultaneously considered, namely, a value with a good theoretical effect is calculated according to historical transportation data, and a wire arrangement result with the lowest cost can be obtained under the condition of guaranteeing the time effect. The historical transportation data are used for acquiring the operation time between the historical stations and the operation time in the historical stations, namely the historical resource consumption of the historic station between the station time of the destination station and the destination station, so that the completion time of the transportation task can be accurately calculated. By this time, warehouse operation time is reversed to drive the warehouse. And by combining the historical transportation data, the positioning data and the truck navigation are received, the in-transit time length and the in-station operation time length (in-station consumption time length) are predicted, the accurate prediction of future multiple lines can be performed in a rolling mode, and the accurate prediction time for receiving and picking up goods at the subsequent stations is provided.

The following describes a transportation route planning method provided in the present specification by taking an application of the transportation route planning method in a vegetable transportation scenario as an example with reference to fig. 3. Fig. 3 is a flowchart of a process of a method for planning a transportation route according to an embodiment of the present disclosure, which specifically includes the following steps.

Step 302, receiving a vegetable transportation task of a target object in a target time period, wherein the vegetable transportation task comprises the purpose space-time information of each vegetable to be transported.

Step 304, identifying a transportation identifier of the vegetable transportation task.

And 306, determining destination sites of the vegetables to be transported according to destination site identifiers contained in the destination space-time information of the vegetables to be transported under the condition that the transportation identifiers are dynamic transportation identifiers.

The dynamic transportation mark represents that the variation between the transportation task and the historical transportation task is larger than a preset value.

Step 308, acquiring historical transportation data corresponding to destination sites of the vegetables to be transported.

Step 310, according to the destination space-time information of each vegetable to be transported, the vegetable transportation quantity of each destination site is counted.

Optionally, the destination spatiotemporal information includes destination site identification;

According to the destination space-time information of each vegetable to be transported, the vegetable transportation quantity of each destination site is counted, and the method comprises the following steps:

And determining the destination space-time information quantity of the destination site identification representing the destination site aiming at any destination site, and determining the destination space-time information quantity as the vegetable traffic of the destination site.

Optionally, the transportation task further comprises a transportation type identifier, wherein the destination site identifier comprises a destination end point identifier or a destination starting point identifier, and the destination site is a destination end point or a destination starting point of vegetable transportation;

for any destination site, determining the destination space-time information quantity of destination site identification representing the destination site, and determining the quantity as the vegetable traffic quantity of the destination site, comprising:

under the condition that the transportation type identifier is a purchase identifier, determining the destination space-time information quantity of the destination represented by the destination identifier, and determining the destination space-time information quantity as the vegetable transportation quantity of the destination;

and under the condition that the transportation type identifier is the return identifier, determining the destination space-time information quantity of the destination starting point characterized by the destination starting point identifier, and determining the destination space-time information quantity as the vegetable transportation quantity of the destination starting point.

Step 312, predicting and obtaining the station consumption time of each destination station in the target time period according to the historical station time of each destination station and the vegetable traffic of each destination station.

Optionally, the historical on-site time includes a historical on-site time and a historical off-site time, and the historical transportation data further includes historical vegetable transportation amounts of each destination site;

according to the historical station duration of each destination station and the vegetable traffic volume of each destination station, predicting to obtain the station consumption duration of each destination station in the target time period, wherein the method comprises the following steps:

Predicting and obtaining the historical processing time of the unit vegetables in the first destination site according to the historical arrival time, the historical arrival time and the historical vegetable traffic of the first destination site, wherein the first destination site is any destination site;

And predicting the consumption time of the first destination station in the station within the target time period according to the historical processing time of the unit vegetables in the first destination station and the vegetable traffic.

And step 314, predicting and obtaining the inter-station resource consumption of each destination station in the target time period according to the historical resource consumption of each destination station.

Step 316, determining the transportation route of the target object in the target time period according to the destination arrival time, the consumption duration in the station and the consumption amount of the resources between the stations.

Optionally, the inter-station resource consumption includes an inter-station consumption time period or an inter-station cost consumption;

determining a transportation route of the target object in the target time period according to the destination arrival time, the in-station consumption time and the inter-station resource consumption amount, wherein the method comprises the following steps of:

Under the condition that the selection instruction carries the aging identifier, determining a transportation route of the target object in the target time period according to the destination arrival time, the consumption time in the station and the consumption time between stations;

And under the condition that the selection instruction carries the cost identifier, determining the transportation route of the target object in the target time period according to the destination arrival time, the consumption duration in the station and the cost consumption between the stations.

Optionally, before receiving the instruction of selecting the route planning mode sent by the client, the method further includes:

Calculating the total consumed time corresponding to each transport route to be selected according to the consumed time in the stations and the consumed time between the stations;

calculating the total cost consumption corresponding to each transport route to be selected according to the cost consumption among stations;

And sending the total consumption time and the total cost consumption corresponding to each transport route to be selected to the client for display so that a user can select a route planning mode according to the total consumption time and the total cost consumption corresponding to each transport route to be selected.

Optionally, determining the transportation route of the target object in the target time period according to the historical transportation data and the vegetable transportation quantity of each destination site includes:

Under the condition that the transportation type identifier is a purchase identifier, a warehouse site is taken as a starting point, and a transportation route of a target object in a target time period is determined according to historical transportation data and the vegetable transportation quantity of each destination end point;

and under the condition that the transportation type identifier is a return identifier, determining a transportation route of the target object in the target time period by taking the warehouse site as an end point according to the historical transportation data and the vegetable transportation quantity of each destination starting point.

Step 318, receiving the planning additional parameter sent by the client.

And 320, determining a transportation route of the target object in the target time period according to the historical transportation data, the vegetable transportation quantity of each destination site and the planned additional parameters.

And step 322, acquiring a re-carved route according to the vegetable transportation task under the condition that the transportation identifier is a static transportation identifier.

The static transportation mark represents that the variation between the transportation task and the historical transportation task is smaller than or equal to a preset value, and the re-carved route is any historical transportation route;

Step 324, determining the similarity between the plurality of historical sites and each destination site contained in the re-route.

Step 326, if the similarity is greater than a preset similarity threshold, determining, for any destination station, whether the re-route includes the destination station.

And 328, determining the transportation route of the target object in the target time period according to the judging result.

And 330, if the similarity is smaller than or equal to the similarity threshold value, determining a transport surface corresponding to the re-engraving route.

And 332, identifying whether the transportation surface contains the destination site or not according to any destination site, and determining the transportation route of the target object in the target time period according to the identification result.

And 334, calculating a transportation index corresponding to the transportation route, and sending the transportation route and the transportation index to the client for display.

According to the transportation route planning method provided by the specification, the transportation route corresponding to the target object is determined through the historical transportation data and the vegetable transportation quantity of each destination site, so that the difference caused by manual wire arrangement is avoided, the efficiency and the accuracy of transportation route planning can be effectively improved, and the target transportation route can be accurately determined through the historical transportation data.

Corresponding to the above method embodiments, the present disclosure further provides an embodiment of a transportation route planning device, and fig. 4 shows a schematic structural diagram of a transportation route planning device provided in one embodiment of the present disclosure. As shown in fig. 4, the apparatus includes:

a receiving module 402 configured to receive a transportation task of a target object within a target time period, wherein the transportation task includes destination space-time information of each cargo to be transported;

The statistics module 404 is configured to obtain historical transportation data according to the destination space-time information of each cargo to be transported, and to count cargo transportation amount of each destination site;

A determining module 406 is configured to determine a transportation route of the target object within the target time period according to the historical transportation data and the cargo transportation volume of each destination site.

In one or more alternative embodiments of the present specification, the destination spatiotemporal information includes destination site identification;

the statistics module 404 is further configured to:

In one or more alternative embodiments of the present disclosure, the historical transportation data includes historical time-to-station durations of each destination site and historical resource consumption between each destination site;

The determining module 406 is further configured to:

In one or more optional embodiments of the present disclosure, the historical on-station time includes a historical on-station time, a historical off-station time, and the historical transportation data further includes historical cargo traffic for each destination station;

The determining module 406 is further configured to:

In one or more alternative embodiments of the present specification, the inter-station resource consumption includes an inter-station consumption period or an inter-station cost consumption;

The determining module 406 is further configured to:

In one or more alternative embodiments of the present description, the determining module 406 is further configured to:

In one or more optional embodiments of the present disclosure, the transportation task further includes a transportation type identifier, the destination spatiotemporal information includes a destination identifier or a destination starting point identifier, and the destination site is a destination or a destination starting point of the cargo transportation;

the statistics module 404 is further configured to:

In one or more alternative embodiments of the present description, the apparatus further comprises an identification module configured to:

Identifying a transportation identifier of the transportation task;

the obtaining module 404 is further configured to:

In one or more alternative embodiments of the present description, the apparatus further comprises a replication module configured to:

In one or more alternative embodiments of the present specification, the re-engraving module is further configured to:

The transportation route planning device provided by the specification receives a transportation task of a target object in a target time period, wherein the transportation task comprises destination space-time information of goods to be transported, acquires historical transportation data according to the destination space-time information of the goods to be transported, counts the goods transportation quantity of each destination site, and determines a transportation route of the target object in the target time period according to the historical transportation data and the goods transportation quantity of each destination site. The historical transportation data and the cargo transportation amount of each destination site are used for determining the target transportation route corresponding to the target object in the target time period, so that the difference caused by manual wire arrangement is avoided, the efficiency and the accuracy of transportation route planning can be effectively improved, and the transportation route can be accurately determined through the historical transportation data.

The above is a schematic solution of a transportation route planning device of the present embodiment. It should be noted that, the technical solution of the transportation route planning device and the technical solution of the transportation route planning method belong to the same concept, and details of the technical solution of the transportation route planning device, which are not described in detail, can be referred to the description of the technical solution of the transportation route planning method.

Fig. 5 illustrates a block diagram of a computing device 500 provided in one embodiment of the present description. The components of the computing device 500 include, but are not limited to, a memory 510 and a processor 520. Processor 520 is coupled to memory 510 via bus 530 and database 550 is used to hold data.

Computing device 500 also includes access device 540, access device 540 enabling computing device 500 to communicate via one or more networks 560. Examples of such networks include public switched telephone networks (PSTN, public Switched Telephone Network), local area networks (LAN, local Area Network), wide area networks (WAN, wide Area Network), personal area networks (PAN, personal Area Network), or combinations of communication networks such as the internet. The access device 540 may include one or more of any type of network interface, wired or wireless, such as a network interface card (NIC, network Interface Controller), such as an IEEE802.11 wireless local area network (WLAN, wireless Local Area Network) wireless interface, a worldwide interoperability for microwave access (Wi-MAX, worldwide Interoperability for Microwave Access) interface, an ethernet interface, a universal serial bus (USB, universal Serial Bus) interface, a cellular network interface, a bluetooth interface, a Near Field Communication (NFC) interface, and so forth.

In one embodiment of the present description, the above-described components of computing device 500, as well as other components not shown in FIG. 5, may also be connected to each other, such as by a bus. It should be understood that the block diagram of the computing device shown in FIG. 5 is for exemplary purposes only and is not intended to limit the scope of the present description. Those skilled in the art may add or replace other components as desired.

Computing device 500 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., tablet, personal digital assistant, laptop, notebook, netbook, etc.), mobile phone (e.g., smart phone), wearable computing device (e.g., smart watch, smart glasses, etc.), or other type of mobile device, or a stationary computing device such as a desktop computer or PC. Computing device 500 may also be a mobile or stationary server.

Wherein the processor 520 is configured to execute computer-executable instructions that, when executed by the processor, perform the steps of the transportation route planning method described above.

The foregoing is a schematic illustration of a computing device of this embodiment. It should be noted that, the technical solution of the computing device and the technical solution of the above transportation route planning method belong to the same concept, and details of the technical solution of the computing device, which are not described in detail, can be referred to the description of the technical solution of the above transportation route planning method.

An embodiment of the present disclosure also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the transportation route planning method described above.

The above is an exemplary version of a computer-readable storage medium of the present embodiment. It should be noted that, the technical solution of the storage medium and the technical solution of the above transportation route planning method belong to the same concept, and details of the technical solution of the storage medium, which are not described in detail, can be referred to the description of the technical solution of the above transportation route planning method.

An embodiment of the present disclosure also provides a computer program, wherein the computer program, when executed in a computer, causes the computer to perform the steps of the above-described transportation route planning method.

The above is an exemplary version of a computer program of the present embodiment. It should be noted that, the technical solution of the computer program and the technical solution of the above transportation route planning method belong to the same concept, and details of the technical solution of the computer program, which are not described in detail, can be referred to the description of the technical solution of the above transportation route planning method.

The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

The computer instructions include computer program code that may be in source code form, object code form, executable file or some intermediate form, etc. The computer readable medium may include any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth.

It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of combinations of actions, but it should be understood by those skilled in the art that the embodiments are not limited by the order of actions described, as some steps may be performed in other order or simultaneously according to the embodiments of the present disclosure. Further, those skilled in the art will appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily all required for the embodiments described in the specification.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to the related descriptions of other embodiments.

The preferred embodiments of the present specification disclosed above are merely used to help clarify the present specification. Alternative embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the teaching of the embodiments. The embodiments were chosen and described in order to best explain the principles of the embodiments and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. This specification is to be limited only by the claims and the full scope and equivalents thereof.

Claims

1. A transportation route planning method, comprising:

Receiving a transportation task of a target object in a target time period, wherein the transportation task comprises destination space-time information of each goods to be transported, and the destination space-time information comprises destination arrival time;

Acquiring historical transportation data according to the destination space-time information of the goods to be transported and counting the goods transportation quantity of each destination site, wherein the historical transportation data comprises the historical site-in time length of each destination site and the historical resource consumption quantity among the destination sites;

The method comprises the steps of determining a transportation route of a target object in a target time period according to historical transportation data and cargo transportation amounts of destination sites, wherein the step of determining the transportation route of the target object in the target time period according to the historical transportation data and the cargo transportation amounts of the destination sites comprises the steps of predicting and obtaining in-site consumption time of the destination sites in the target time period according to historical in-site time of the destination sites and the cargo transportation amounts of the destination sites, predicting and obtaining inter-site resource consumption of the destination sites in the target time period according to historical resource consumption among the destination sites, and determining the transportation route of the target object in the target time period according to destination arrival time, in-site consumption time and inter-site resource consumption.

2. The method of claim 1, the destination spatiotemporal information comprising destination site identification;

the step of obtaining historical transportation data according to the destination space-time information of each cargo to be transported comprises the following steps:

3. The method of claim 1, the historical on-site time comprising a historical on-site time, a historical off-site time, the historical shipping data further comprising historical cargo traffic for each destination site;

The predicting, according to the historical on-station duration of each destination station and the cargo traffic volume of each destination station, the on-station consumption duration of each destination station in the target time period includes:

4. The method of claim 1, the inter-station resource consumption comprising an inter-station consumption duration or an inter-station cost consumption;

The determining a transportation route of the target object in the target time period according to the destination arrival time, the intra-station consumption duration and the inter-station resource consumption amount comprises the following steps:

5. The method according to claim 4, further comprising, before the receiving the instruction for selecting the route planning manner by the user sent by the client:

6. The method of claim 1, wherein the transportation task further comprises a transportation type identifier, wherein the destination spatiotemporal information comprises a destination end identifier or a destination origin identifier, and wherein the destination site is a destination end or a destination origin of the transportation of the cargo;

According to the destination space-time information of each cargo to be transported, the cargo transportation amount of each destination site is counted, including:

7. The method of claim 6, wherein determining the transportation route of the target object within the target time period according to the historical transportation data and the cargo traffic of each destination site comprises:

8. The method of claim 1, further comprising, prior to said obtaining historical transportation data based on said destination spatiotemporal information for each of said goods to be transported:

Identifying a transportation identifier of the transportation task;

9. The method of claim 8, the method further comprising:

10. The method according to claim 9, wherein the determining, according to the route planning policy corresponding to the similarity, the transportation route of the target object in the target time period according to the resculpting route and the destination sites includes:

11. A transportation route planning device comprising:

The system comprises a receiving module, a processing module and a processing module, wherein the receiving module is configured to receive a transportation task of a target object in a target time period, wherein the transportation task comprises destination space-time information of each goods to be transported, and the destination space-time information comprises destination arrival time;

The statistics module is configured to acquire historical transportation data according to the destination space-time information of the goods to be transported and to count the goods transportation quantity of each destination site, wherein the historical transportation data comprises the historical site-in time length of each destination site and the historical resource consumption quantity among the destination sites;

The determining module 406 is further configured to predict and obtain a time consumption of each destination station in the target time period according to a historical time of each destination station and the cargo traffic of each destination station, predict and obtain a resource consumption of each destination station in the target time period according to a historical resource consumption among the destination stations, and determine a transportation route of the target object in the target time period according to the destination arrival time, the time consumption of each destination station and the resource consumption among the destination stations.

12. A computing device, comprising:

A memory and a processor;

The memory is configured to store computer executable instructions that, when executed by the processor, implement the steps of the transportation route planning method of any one of claims 1 to 10.

13. A computer readable storage medium storing computer executable instructions which when executed by a processor implement the steps of the transportation route planning method of any one of claims 1 to 10.