CN114693199A

CN114693199A - Logistics order information processing method, device, equipment and storage medium

Info

Publication number: CN114693199A
Application number: CN202011612600.5A
Authority: CN
Inventors: 陈凯; 陈冠岭
Original assignee: Nanjing Fuyou Online E Commerce Co ltd
Current assignee: Jiangsu Zhijian Logistics Co ltd
Priority date: 2020-12-29
Filing date: 2020-12-29
Publication date: 2022-07-01
Anticipated expiration: 2040-12-29
Also published as: CN114693199B

Abstract

The present application discloses a method, device, device and storage medium for processing logistics order information. The method includes obtaining multiple orders with the same origin, destination, transport model and delivery time among the orders currently issued by the same user, and obtaining quotation information of multiple orders according to the information combined with the relational curve database and the neighboring quotation table, Thereafter, the multiple orders are screened by using the quotation information, the order with the smallest difference between the order price and the quotation information among the multiple orders is reserved, and the other orders are cancelled. This application solves the problems of resource occupation, user loss and poor user experience caused by issuing multiple orders for the same freight demand.

Description

Logistics order information processing method, device, equipment and storage medium

Technical Field

The application relates to the technical field of logistics, in particular to a method, a device, equipment and a storage medium for logistics order information processing.

Background

At present, in the field of logistics, particularly in the field of truck freight, due to the characteristics of truck freight, the transport mileage is generally long, so that the price of an order is highly restricted by factors such as seasons, geography and weather, and the price of the order is difficult to determine. At present, a platform for order information distribution exists in a network, and a user can distribute own order information on the platform and wait for other users to receive orders. However, at present, the price of an order is difficult to determine, so that a user often issues a plurality of orders with different prices according to a certain freight transportation requirement of the user, and further, the time for the user to wait for the order to be filled is reduced, or the user cancels the previously filled order with a lower price after waiting for the order with a higher price to be filled.

For the case that a user issues multiple orders for a shipping requirement, the inventor finds that many problems arise: one is the problem of resource occupation, only one order in a plurality of orders is finally committed, and other orders which are not committed inevitably cancel the issuance of the order at last, so that processing resources, storage resources, network resources and the like are inevitably occupied during the issuance of the order, and great waste is caused; meanwhile, due to the limited resources of the order display, the experience of other users intending to receive orders can be influenced. Secondly, some users cancel the previously committed orders with lower price after waiting for the orders with higher price to commit, which may cause loss to the order receiving users. If the user is pulled into the blacklist or the user is restricted from issuing an order, these approaches cannot not only fundamentally solve the above problems, but also affect the user experience. Therefore, how to solve the problems of resource occupation, user loss and poor user experience caused by issuing a plurality of orders with the same freight transportation requirement is urgent to solve.

Disclosure of Invention

The main purpose of the present application is to provide a method for processing logistics order information, so as to solve the problems of resource occupation, user loss and poor user experience caused by issuing multiple orders in the same freight transportation requirement.

In order to achieve the above object, according to a first aspect of the present application, there is provided a method of logistics order processing, comprising:

acquiring a plurality of orders with the same origin, destination, transport vehicle type and delivery time in the orders currently issued by the same user; obtaining a first mileage according to the origin and destination of the orders; obtaining a target basic route and a second mileage according to the origin, the destination and the transport vehicle type of the orders; obtaining a corresponding relation curve from a relation curve database according to the transportation vehicle types of the orders; obtaining a first single-kilometer quoted price according to the relation curve and the first mile; obtaining a second single-kilometer quoted price according to the relation curve and the second mileage; obtaining a third single-kilometer quotation according to the target basic line and the neighbor quotation table; dividing the product of the first single-kilometer quoted price and the third single-kilometer quoted price by the second single-kilometer quoted price to obtain a final single-kilometer quoted price; taking the product of the final single-kilometer quoted price and the first mile as a quoted price; and reserving one order with the order price closest to the quoted price in the plurality of orders, and canceling the release of other orders.

Further, the method further comprises: and establishing a neighbor quotation table according to the origin, the destination, the transportation vehicle type, the neighbor lines of the transportation line and the single-kilometer freight rate of the neighbor lines in the historical order.

Further, the establishing a neighbor price list according to the origin, the destination, the transportation vehicle type, the neighbor lines of the transportation line and the single-kilometer freight rate of the neighbor lines in the historical order comprises: obtaining a plurality of historical orders, and grouping the historical orders according to the starting place and the destination of each line in a road transportation line table and by combining transportation vehicle types, wherein each group corresponds to a basic line; determining the number of orders, the average value of the transport mileage and the single kilometer freight rate corresponding to each basic line according to the historical orders in each group; determining all adjacent lines corresponding to each basic line according to the transport vehicle type, the origin and the destination of the basic lines; calculating the average value difference of the transport mileage, the originating mileage difference and the destination mileage difference between each adjacent line and the corresponding basic line; obtaining a weighted mileage difference of each adjacent line according to the origin mileage difference, the destination mileage difference, the transportation mileage average difference and the weight thereof, and calculating a mileage weight coefficient of each adjacent line according to the weighted mileage difference; calculating an order confidence coefficient of each neighboring line according to the historical order quantity corresponding to each neighboring line; obtaining the neighbor coefficient of each neighbor line according to the mileage weight coefficient and the order confidence coefficient of each neighbor line; obtaining single-kilometer quoted price of each basic line according to the neighbor coefficient of the neighbor line and the single-kilometer freight price; and establishing a neighbor quotation table according to the corresponding relation between each basic line and the single-kilometer quotation.

Further, the method further comprises: and establishing a relational curve database according to the transport mileage, the single-kilometer freight rate and the transport vehicle type in the historical order.

Further, the establishing a relational database according to the transportation mileage, the single-kilometer transportation price and the transportation vehicle type in the historical order includes: determining the mileage characteristics and the single-kilometer freight rate in each data set according to the transport mileage data, the single-kilometer freight rate data and the transport vehicle type data in the historical order, wherein each data set corresponds to one group, and different groups correspond to different transport vehicle types; fitting the mileage characteristics and the single-kilometer freight rate in each data set by using a regression algorithm to obtain a relation curve between the transport mileage and the single-kilometer freight rate in each group; and establishing a relation curve database by utilizing the corresponding relation between the transportation vehicle type data and the relation curve.

In order to achieve the above object, according to a second aspect of the present application, there is provided a method of logistics order processing, comprising:

acquiring an origin, a destination and a transportation vehicle type uploaded by a user side; obtaining a first mileage according to an origin and a destination; obtaining a target basic route and a second mileage according to the origin, the destination and the vehicle type; obtaining a corresponding relation curve from a relation curve database according to the type of the transportation vehicle; obtaining a first single-kilometer quoted price according to the relation curve and the first mile; obtaining a second single-kilometer quoted price according to the relation curve and the second mileage; obtaining a third single-kilometer quotation according to the target basic line and the neighbor quotation table; dividing the product of the first single-kilometer quotation and the third single-kilometer quotation by the second single-kilometer quotation to obtain a final single-kilometer quotation; taking the product of the final single-kilometer quoted price and the first mile as a quoted price; and sending the quotation to the user side, and displaying the quotation for the user by the user side.

In order to achieve the above object, according to a third aspect of the present application, there is provided a logistics order information processing apparatus comprising:

the order acquisition module is used for acquiring a plurality of orders with the same origin, destination, transport vehicle type and delivery time in the orders currently issued by the same user;

the mileage determining module is used for obtaining a first mileage according to the starting place and the destination of the orders; obtaining a target basic route and a second mileage according to the origin, the destination and the transport vehicle type of the orders; obtaining a corresponding relation curve from a relation curve database according to the transportation vehicle types of the orders;

the single-kilometer quotation determining module is used for obtaining a first single-kilometer quotation according to the relation curve and the first mileage; obtaining a second single-kilometer quoted price according to the relation curve and the second mileage; obtaining a third single-kilometer quotation according to the target basic line and the neighbor quotation table;

the quotation confirms the module, is used for dividing the product of quotation of the second single kilometer with the quotation of the third single kilometer of the first single kilometer, receive the final single kilometer quotation; taking the product of the final single-kilometer quoted price and the first mile as a quoted price;

and the order processing module is used for reserving one order with the order price closest to the quoted price in the orders and canceling the release of other orders.

In order to achieve the above object, according to a fourth aspect of the present application, there is provided a logistics order information processing apparatus comprising:

the system comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for acquiring an origin, a destination and a transportation vehicle type uploaded by a user side;

the mileage module is used for obtaining a first mileage according to an origin and a destination; obtaining a target basic route and a second mileage according to the origin, the destination and the vehicle type; obtaining a corresponding relation curve from a relation curve database according to the type of the transportation vehicle;

the freight rate module is used for obtaining a first single-kilometer quoted price according to the relation curve and the first mileage; obtaining a second single-kilometer quoted price according to the relation curve and the second mileage; obtaining a third single-kilometer quotation according to the target basic line and the neighbor quotation table;

the quotation module is used for dividing the product of the first single-kilometer quotation and the third single-kilometer quotation by the second single-kilometer quotation to obtain the final single-kilometer quotation; taking the product of the final single-kilometer quoted price and the first mile as a quoted price;

and the display module is used for sending the quotation to the user side, and the user side displays the quotation for the user.

In order to achieve the above object, according to a fifth aspect of the present application, there is provided a computer-readable storage medium storing computer instructions for causing the computer to execute the neighbor-quote-table-based transportation order processing method according to any one of the first or second aspects.

In order to achieve the above object, according to a sixth aspect of the present application, there is provided an electronic apparatus comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores a computer program executable by the at least one processor to cause the at least one processor to perform the method of neighboring-quote-table-based transport order processing of any of the above first aspects.

In the method and the device for processing the logistics order information, for a plurality of orders of the same user, the quotation information of the plurality of orders can be obtained according to the information by combining the relational curve database and the neighbor quotation table, then the plurality of orders are screened by utilizing the quotation information, one order with the minimum difference between the order price and the quotation information in the plurality of orders is reserved, and other orders are cancelled. Therefore, the order quantity of the same freight requirement can be controlled, and the problems of resource occupation, user loss and poor user experience caused by the fact that a plurality of orders are issued by the same freight can be effectively solved. In addition, the corresponding relation between the basic line and the single-kilometer quoted price in the embodiment of the application is calculated according to the adjacent line corresponding to the historical orders and the single-kilometer freight rate, so that the single-kilometer transportation quoted price obtained according to the adjacent quoted price table is reasonable, the order with the minimum difference value with the transportation quoted price is reserved, the market order can be maintained, the order transaction speed can be balanced, and the user experience is improved. In addition, because the corresponding relation between the basic line and the single-kilometer quoted price is calculated according to the adjacent line corresponding to the historical order and the single-kilometer freight price thereof, even if the historical order is less or no historical order is available on the transportation line of the order, the more accurate quoted price can be provided.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this application, serve to provide a further understanding of the application and to enable other features, objects, and advantages of the application to be more apparent. The drawings and their description illustrate the embodiments of the invention and do not limit it. In the drawings:

fig. 1 is a flowchart of a method for processing logistics order information according to an embodiment of the present application;

fig. 2 is a flowchart of a method for processing logistics order information according to an embodiment of the present application;

fig. 3 is a schematic structural diagram of a logistics order information processing apparatus according to an embodiment of the present application;

fig. 4 is a schematic structural diagram of a logistics order information processing apparatus according to an embodiment of the present application.

Detailed Description

In order to make the technical solutions of the present application better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the accompanying drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be used. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.

The present application provides a method for processing a logistics order, which is shown in the flow chart of a method for processing logistics order information shown in fig. 1; the method comprises the following steps:

acquiring a plurality of orders with the same origin, destination, transport vehicle type and delivery time in the orders currently issued by the same user;

obtaining a first mileage according to the origin and destination of the orders;

obtaining a target basic route and a second mileage according to the origin, the destination and the transportation vehicle type of the orders;

obtaining a corresponding relation curve from a relation curve database according to the transportation vehicle types of the orders;

obtaining a first single-kilometer quoted price according to the relation curve and the first mile;

obtaining a second single-kilometer quoted price according to the relation curve and the second mileage;

obtaining a third single-kilometer quotation according to the target basic line and the neighbor quotation table;

dividing the product of the first single-kilometer quoted price and the third single-kilometer quoted price by the second single-kilometer quoted price to obtain a final single-kilometer quoted price;

taking the product of the final single-kilometer quoted price and the first mile as a quoted price;

and reserving one order with the order price closest to the quoted price in the plurality of orders, and canceling the release of other orders.

For better understanding, the following further description is provided:

s101, obtaining a plurality of orders with the same origin, destination, transport vehicle type and delivery time in the orders currently issued by the same user.

The server or the background system and other execution equipment can judge whether a plurality of orders with the same origin, destination, transport vehicle type and delivery time exist in each order currently issued by the same user, and if yes, the plurality of orders are obtained; wherein, a plurality of orders refers to two or more orders.

S102, obtaining a first mileage according to the starting places and the destination places of the orders; obtaining a target basic route and a second mileage according to the origin, the destination and the transportation vehicle type of the orders; and obtaining a corresponding relation curve from a relation curve database according to the transportation vehicle types of the orders.

Obtaining a first mileage according to the origin and the destination of the plurality of orders, wherein the mileage of the shortest driving path between the origin and the destination of the plurality of orders can be used as the first mileage; more specifically, since the origin and the destination of the orders are the same, the position information of the origin and the destination can be obtained, and then the current shortest driving route between the two places can be obtained by means of navigation, route planning and other technologies, and the mileage of the route is taken as the first mileage.

Obtaining the target basic route according to the origin, the destination and the transportation vehicle type of the plurality of orders, which may be to determine one target basic route, that is, the target basic route corresponding to the plurality of orders, according to the origin, the destination and the transportation vehicle type, for example, assuming that the origin in the plurality of orders is beijing, the destination is shanghai, and the transportation vehicle type is a 9.6 m van, the target basic route is: Beijing-Shanghai, 9.6 m van.

The second mileage is obtained according to the origin, the destination and the transportation vehicle type of the multiple orders, and may be that a target basic route is determined according to the origin, the destination and the transportation vehicle type, a plurality of corresponding historical orders (i.e., historical orders with the same origin, destination and transportation vehicle type) are obtained according to the target basic route, and the average value of the transportation mileage of the multiple historical orders is taken as the second mileage. For example, assuming that the origin of the orders is beijing, the destination is shanghai, and the transportation vehicle type is 9.6 meters van, the target basic route is: the method comprises the following steps that a Beijing-Shanghai van and a 9.6-meter van can be used for obtaining a plurality of corresponding historical orders according to a target basic line, obtaining the respective transportation mileage of the historical orders, and taking the average value of the transportation mileage as a second mileage; it should be noted that the process of acquiring the second mileage is the same as the process of acquiring the average value of the mileage of the basic line in the establishment of the neighboring quotation table, so the process can also directly utilize the average value of the mileage of the basic line in the neighboring quotation table; in addition, the neighbor bid table and the establishment process thereof will be described later.

Obtaining a corresponding relation curve from a relation curve database according to the transportation vehicle types of the plurality of orders, wherein the relation curve corresponding to the transportation vehicle types can be selected from the relation curve database according to the transportation vehicle types of the plurality of orders; it should be noted that there are multiple relationship curves in the relationship curve database, each transportation vehicle type corresponds to one transportation vehicle type, each relationship curve has a corresponding relationship between mileage and quoted price, and the relationship curve database and the establishment process thereof will be described later.

S103, obtaining a first single-kilometer quoted price according to the relation curve and the first mile; obtaining a second single-kilometer quoted price according to the relation curve and the second mileage; and obtaining a third single-kilometer quotation according to the target basic line and the neighbor quotation table.

The first single-kilometer offer is obtained according to the relationship curve and the first mileage, and the single-kilometer running price corresponding to the first mileage can be obtained according to the corresponding relationship between the mileage on the relationship curve and the single-kilometer running price, and the single-kilometer running price is used as the first single-kilometer offer.

And obtaining a second single-kilometer quote according to the relationship curve and the second mileage, wherein the single-kilometer running price corresponding to the second mileage can be obtained according to the corresponding relationship between the mileage on the relationship curve and the single-kilometer running price, and the single-kilometer running price is used as the second single-kilometer quote.

And obtaining a third single-kilometer quoted price according to the target basic line and the neighbor quoted price table, wherein the basic line with the same transport vehicle type, origin and destination in the neighbor quoted price table is determined by utilizing the transport vehicle type, origin and destination in the target basic line, and the third single-kilometer quoted price corresponding to the target basic line is obtained by combining the corresponding relation between the basic line and the single-kilometer quoted price. Since the target basic line has been determined before, and the target basic line can be corresponded to the basic line in the neighbor quotation table by the same vehicle type, origin and destination, and the neighbor quotation table has the corresponding relationship between the basic line and the single-kilometer quotation, the corresponding relationship between the target basic line and the single-kilometer quotation is obtained, and the third single-kilometer quotation corresponding to the target basic line is obtained.

S104, dividing the product of the first single-kilometer quotation and the third single-kilometer quotation by the second single-kilometer quotation to obtain a final single-kilometer quotation; and taking the product of the final single-kilometer quote and the first mile as a quote.

Which may be a mixture of at least one of,

final single kilometer quoted price x first mile

S105, one order with the price closest to the price of the quoted price in the orders is reserved, and the release of other orders is cancelled.

When a user issues an order, the order price is given in each order. And the service background processes the multiple orders according to the quoted prices obtained in the mode, specifically, the difference value between the price of each order and the quoted price is calculated respectively, the order with the minimum difference value between the price of the order and the quoted price is finally reserved according to the multiple difference results, the release of other orders is cancelled, and the cancelled message is returned to the user side so as to inform the user.

The method for establishing the relational curve database is described below.

The relational curve database is established according to the transport mileage, the single-kilometer freight rate and the transport vehicle type in the historical order. The relational curve database comprises the corresponding relational curves of different transportation vehicle types, so that the corresponding relational curves can be determined according to the transportation vehicle types. And the relation curve is a relation curve between the transport mileage and the single-kilometer freight rate obtained by fitting the mileage characteristics corresponding to the historical orders and the single-kilometer freight rate by using a regression algorithm.

The relational database is established in advance, and needs to be established before the process of obtaining the corresponding relational curve from the relational curve database according to the transportation vehicle types of the orders is completed, wherein the specific establishment flow of the relational database is as follows:

step a 1: and determining the mileage characteristics and the single-kilometer freight rate in each data set according to the transport mileage data, the single-kilometer freight rate data and the transport vehicle type data in the historical order, wherein each data set corresponds to one group, and different groups correspond to different transport vehicle types.

The method comprises the following steps of determining the mileage characteristics and the single-kilometer freight rate in each data set, wherein the specific implementation flow is as follows:

step a 11: acquiring the transport mileage data, the single-kilometer freight rate data and the transport vehicle type data of a plurality of historical orders;

in particular, the method comprises the following steps of,

since all data about the historical order (completed normal transportation order) is contained in the historical order, various data of the historical order can be directly obtained from a system or a storage device; what is needed here is haul mileage data, single kilometer freight rate data, and haul vehicle type data for historical orders.

The transport mileage data is the travel mileage of the vehicle in the actual transport process, the numerical value of the transport mileage data is the existing numerical value in the order, if some orders do not have the numerical value, the travel track can be obtained on the map by using the continuous vehicle positioning information recorded in the order, and the transport mileage data can be obtained according to the track.

The value of the single kilometer freight rate data is usually the value of the single kilometer freight rate data in the order, and if the value is not available in some orders, the single kilometer freight rate data can also be obtained by dividing the order price by the transport mileage.

The transportation vehicle type data is vehicle data for carrying the order, and the transportation vehicle type information may include any one or a combination of the following: vehicle model, vehicle length, vehicle upper load limit.

Step a 12: grouping a plurality of historical orders according to transport vehicle types;

in particular, the method comprises the following steps of,

since the transportation vehicle type data in a plurality of historical orders are obtained before, the historical orders can be grouped according to the transportation vehicle type data; such as grouping the historical orders by vehicle length or by vehicle length and upper vehicle load limit.

Step a 13: characterizing the transport mileage in each historical order to generate mileage characteristics;

since the shipping mileage in each historical order has been previously obtained, the shipping mileage can be characterized to obtain corresponding mileage characteristics. The specific method can be as follows:

the method comprises the following steps:

inputting the transport mileage into a feature function to generate corresponding mileage features; wherein the characteristic function can be any one of the following

1)

2)

3)

4)

In the above formula, x represents the transport mileage, and f represents the mileage characteristic;

in addition to the above-described feature functions, a plurality of similar functions derived may be utilized to generate the mileage feature.

The second method comprises the following steps:

inputting the transport mileage into a plurality of feature functions to generate a plurality of initial mileage features, and splicing or calculating the plurality of initial mileage features to obtain the mileage features corresponding to the transport mileage.

The plurality of feature functions may be any combination of at least two of the first method, and each feature function correspondingly obtains an initial mileage feature. The concrete steps of splicing or calculating the initial mileage characteristics to obtain the mileage characteristics corresponding to the transport mileage are as follows: multiple initial mileage features can be spliced to form a vector as the mileage feature. The following are exemplary: assuming that the transportation mileage of the historical order 1 is 300 km, the initial mileage characteristics calculated by using the formula 1 and the formula 3 are 0.003 and 0.058, respectively, and the mileage characteristics obtained after splicing are [0.003,0.058 ]. The initial mileage can also be calculated to obtain mileage characteristics, such as addition and subtraction, averaging, and the like.

Step a 14: and establishing a corresponding data set according to the group, wherein the data set comprises the mileage characteristics and the single-kilometer freight rate of all historical orders in the group.

In particular, the method comprises the following steps of,

since the historical orders are grouped according to the types of the transportation vehicles, one group can contain a plurality of historical orders, and the mileage characteristics and the single-kilometer freight rate of each historical order are obtained before, a corresponding data set can be established for each group. Illustratively, as shown in Table 1, is a representation of a data set. Including order number, mileage characteristics, and single kilometer rates.

TABLE 1 data set

Order numbering	Mileage characteristics	Freight rate per kilometer
			1001	0.003	5
1002	0.005	3
			1003	0.002	10
…	…	…

For example, as shown in table 2, the data set is another data set representation in which only the mileage feature, the single kilometer freight rate, and the corresponding relationship therebetween are retained, the initial mileage feature X1, the initial mileage feature X2, and the initial mileage feature X3 are initial mileage features of one order, and the mileage feature X is a jointed mileage feature.

Step a 2: fitting the mileage characteristics and the single-kilometer freight rate in each data set by using a regression algorithm to obtain a relation curve between the transport mileage and the single-kilometer freight rate in each group;

specifically, since a plurality of data sets are obtained by grouping, the mile features and the single-kilometer freight rate in each data set can be fitted according to a ridge regression algorithm or a LASSO regression algorithm to obtain an initial relationship curve of the mile features and the single-kilometer freight rate corresponding to each data set; then converting the mileage characteristics on the initial relation curve into transportation mileage according to the corresponding relation between the transportation mileage and the mileage characteristics to obtain a relation curve between the transportation mileage and the single-kilometer freight rate corresponding to each data set; and determining a relation curve between the transport mileage and the single-kilometer freight rate corresponding to each data set as a relation curve between the transport mileage and the single-kilometer freight rate in each group. Illustratively, the abscissa of the relationship curve corresponds to the transportation mileage, and the ordinate of the relationship curve corresponds to the single-kilometer freight rate.

It should be noted that, after testing is performed by using other historical data, it is found that the relationship curve obtained by the ridge regression algorithm or the LASSO regression algorithm has a better effect, and the obtained relationship curve is more in line with the actual situation; in addition, since both the ridge regression algorithm and the LASSO regression algorithm are existing algorithms, and the implementation manner of using the ridge regression algorithm or the LASSO regression algorithm to complete data fitting is also existing, the implementation manner of fitting the mileage feature and the single-kilometer freight rate in each data set according to the ridge regression algorithm or the LASSO regression algorithm is not described in detail here.

Step a 3: and establishing a relation curve database by utilizing the corresponding relation between the transportation vehicle type data and the relation curve.

And correspondingly storing the transportation vehicle type and the obtained relation curve of each group to obtain a relation curve database.

The method for establishing the neighbor quotation table is described as follows.

The neighbor quotation table at least comprises each basic line and the corresponding single-kilometer quotation; the neighbor quotation table is required to be established in advance, the neighbor quotation table is required to be established before the process of obtaining the third single-kilometer quotation according to the target basic line and the neighbor quotation table, and the neighbor quotation table can also be established before the process of obtaining the target basic line and the second kilometer quotation according to the origins, the destinations and the transportation models of the plurality of orders is completed. The neighbor quotation tables are established according to the origin, the destination, the type of the transportation vehicle, the neighbor lines of the transportation line (or the target basic line) and the single-kilometer freight rate of the neighbor lines in the historical orders. The specific establishment process is as follows:

step b 1: obtaining a plurality of historical orders, and grouping the historical orders according to the starting place and the destination of each line in a road transportation line table and by combining transportation vehicle types, wherein each group corresponds to a basic line;

specifically, in order to establish a model capable of accurately providing all road transportation route offers, it is first necessary to determine which of the road transportation routes are available, and a transportation route table, specifically, a national road transportation route table (the national road transportation route table includes all available road transportation routes, such as beijing-shanghai, baoji-nanzhang, and the like) is used to determine the road transportation routes.

The historical orders and the various information contained therein (e.g., origin, destination, shipping mileage, shipping vehicle type, order price, etc.) may then be retrieved from the system and storage device. All historical orders can be acquired, or historical orders generated in a certain time or in a certain time in the history can be acquired, and the acquisition mode is not limited here. The historical orders are grouped after being acquired, and because various information in the historical orders is acquired before, the origin and the destination of each line in a transportation line table are required to be compared with the origin and the destination in the historical orders, and the transportation vehicle type is required to be compared with the transportation vehicle type in the historical orders, so that the historical orders are grouped; that is, historical orders are grouped by origin, destination and vehicle type, thus forming a plurality of groups containing historical orders. The purpose of the grouping is to complete the quote later, i.e. to give a quote on a transport route for one vehicle type. In addition, each group corresponds to a basic line, which is set for convenience of calculation and explanation later, and if the origin is beijing, the destination is shanghai, and the vehicle type is 9.6 meters carriage, the basic line can be expressed as: Beijing-Shanghai, 9.6 m van.

The transportation vehicle type is vehicle data for carrying the order, and the transportation vehicle type information may include any one or a combination of the following: 1) the vehicle model; 2) a vehicle length; 3) upper vehicle load limit. It should be noted that the vehicle type information is considered in the grouping because due to geographical factors, etc., it is likely that the transportation mileage of different vehicle types between the same origin and destination is greatly different, and therefore the quotation process needs to be adjusted accordingly.

Step b 2: determining the number of orders, the average value of the transport mileage and the single kilometer freight rate corresponding to each basic line according to the historical orders in each group;

specifically, since the historical orders in each group are determined in step 1, and each group and each basic line are also in one-to-one correspondence, the number of orders, the average transportation mileage value and the single kilometer freight rate corresponding to each basic line can be obtained according to the historical order data in the group;

it should be noted that the order quantity is the quantity of the historical orders in the group;

the average transport mileage is obtained by dividing the sum of the transport mileage of all historical orders in the group by the number of orders. The transport mileage is the travel mileage of the vehicle in the actual transport process, the numerical value of the transport mileage is the existing numerical value in the order, if some orders do not have the numerical value, the travel track can be obtained on the map by using the continuous vehicle positioning information recorded in the order, and the transport mileage can be obtained according to the track.

The freight rate per kilometer needs to be obtained through calculation, and the embodiment provides a calculation method, wherein a specific calculation formula is as follows:

where n represents the historical order quantity within the group; omega_nThe weight is expressed, and the value of the weight decreases with the increase of the difference between the historical order transaction date and the current date (i.e. the number of days between the historical order transaction date and the current date), and specifically can be

p_nThe unit kilometer freight rate of a certain historical order in the group is represented, and the numerical value of the unit kilometer freight rate of the certain historical order can be obtained by dividing the order price of the historical order by the transport mileage of the historical order.

Step b 3: determining all adjacent lines corresponding to each basic line according to the transport vehicle type, the origin and the destination of the basic lines;

specifically, since the origin and destination of the base line are known, the neighbor line can be determined from the origin and destination of the base line. The neighboring lines in this embodiment may be the following four cases:

the first type is a line with the same transportation vehicle type and the same origin and destination, and only one line is provided; the following are exemplary: if the basic line is Beijing-Shanghai, the adjacent line can only be Beijing-Shanghai;

the second type is a route with the same transport vehicle type, the same origin and different destinations; there may be multiple such lines; the following are exemplary: if the basic line is Beijing-Shanghai, the adjacent line can be Beijing-Kun shan, or Beijing-Suzhou, etc.;

the third is a route with the same transportation vehicle type, different starting places and the same destination; there may be multiple such lines; the following are exemplary: if the basic line is Beijing-Shanghai, the adjacent line can be Tianjin-Shanghai, or Baoding-Shanghai, etc.;

fourthly, the routes are the same in transportation vehicle type and different in both origin and destination, and multiple routes may exist; the following are exemplary: if the base line is Beijing-Shanghai, the neighbor lines may be Tianjin-Suzhou, or Baoding-Kunshan, etc.

It should be noted that, in the above four cases, the transportation vehicle types of the basic line and the neighboring line are the same, and for convenience of description, the transportation vehicle types are omitted in the example, that is, the basic line is originally a beijing-shanghai and 9.6 m van, and is only written as beijing-shanghai, and the neighboring line is originally a baoding-kunshan and 9.6 m van, and is only written as baoding-kunshan; the same is true in the following examples.

For the determination of the neighbor line, a manner is given in this embodiment, which is specifically as follows:

firstly, acquiring all neighbor origins according to the origins of basic lines;

the neighbor origination is the origination of the neighbor line. Specifically, the manner of acquiring all neighbor origins is as follows: the origin of the basic line is used as the neighbor origin, and then the neighbor origin can be obtained according to the previously calculated average values of the mileage of other basic lines, specifically, since the transportation vehicle type is used in the process of grouping, many other basic lines going to the origin can be found under the same transportation vehicle type, and if the average values of the mileage of the other basic lines are less than the first preset distance (or the average values of the mileage of the other basic lines are less than the first preset proportion of the average values of the mileage of the basic lines), the origins of the other basic lines can be used as the neighbor origin. The first preset distance can be adaptively adjusted according to requirements, wherein 200KM is an optimal value; the first preset proportion can also be adaptively adjusted according to requirements, wherein 0.4 is a preferred value.

The above description of obtaining the neighbor originator is made with reference to an example: if the basic line is Beijing-Shanghai, Beijing is the origin of the basic line, so the Beijing can be used as a neighbor origin; in addition, many other basic lines going to Beijing can be found under the same transport vehicle type, such as Tianjin-Beijing, Baoding-Beijing, Shijiazhuang-Beijing, and the like; then, the other basic lines can be selected, if the average value of the transport mileage of the other basic lines, namely the insurance-Beijing, is less than 200KM, the insurance can be used as a neighboring origin; the average of the mileage of other basic routes, such as Shijiazhuang-Beijing, is greater than 200KM, so Shijiazhuang cannot be a neighbor origin. Alternatively, the neighbor origination points may be obtained according to whether the other basic route mileage average value is smaller than the basic route mileage average value 0.4. If the mean transport mileage of the other basic route, Tianjin-Beijing, is less than 0.4, Tianjin can be used as the nearest neighbor origin.

Secondly, acquiring all neighbor destinations according to the destinations of the basic line;

wherein the neighbor destination is a destination of the neighbor line. The specific way to obtain all the neighbor destinations is as follows: the destination of the basic line is taken as a neighbor destination, and then the neighbor destination can also be obtained by using the previously calculated average values of the mileage of other basic lines, because the transportation vehicle type is used in the process of grouping, many other basic lines driven away from the destination can be searched under the same transportation vehicle type, and if the average values of the mileage of the other basic lines are smaller than a second preset distance (or the average values of the mileage of the other basic lines are smaller than a second preset proportion of the average values of the mileage of the basic lines), the destinations of the other basic lines can be taken as the neighbor destination. The second preset distance can be adaptively adjusted according to requirements, wherein 200KM is an optimal value; the second preset proportion can also be adaptively adjusted according to requirements, wherein 0.4 is a preferred value. It should be noted that the first preset distance and the second preset distance may be the same or different; the first predetermined ratio and the second predetermined ratio may be the same or different.

The above description of obtaining the neighbor destination is made with reference to an example: if the basic line is Beijing-Shanghai, Shanghai is the destination of the basic line, the Shanghai can be used as a neighboring destination; in addition, many other basic lines which drive away from Shanghai can be found under the same transport vehicle type, such as Shanghai-Kun shan, Shanghai-Suzhou, Shanghai-Nanjing, and the like; then, the other basic lines can be selected, and if the average value of the transport mileage of the other basic lines is less than 200KM, the Queen mountain can be used as a neighboring destination; if the average value of the mileage transported by other basic lines, shanghai-nanjing, is greater than 200KM, nanjing cannot be used as a near-neighbor destination. Alternatively, the neighbor destinations may be obtained according to whether the other base route mileage average is less than the base route mileage average 0.4. If shanghai-suzhou is the baseline route mileage average 0.4, suzhou may be the neighbor destination.

And finally, matching the adjacent origin with the adjacent destination one by one, and traversing to obtain all adjacent lines.

And matching all the neighbor origins and all the neighbor destinations acquired in the previous step one by one, and traversing all matching results to obtain all the neighbor lines.

Step b 4: calculating the average value difference of the transport mileage, the originating mileage difference and the destination mileage difference between each adjacent line and the corresponding basic line;

all the neighbor lines corresponding to the basic line are determined before, so that the average value difference of the transport mileage between each neighbor line and the basic line can be calculated; if the basic line is Beijing-Shanghai, if the adjacent line is also Beijing-Shanghai, the average difference of the transport mileage of the adjacent line and the basic line is 0; if the neighboring line is a baoding-kunshan, calculating the difference value (such as the value of | X-Y |) between the average value of the transportation mileage of Beijing-Shanghai (such as the value of X) and the average value of the transportation mileage of the basic line of the baoding-kunshan (such as the value of Y); it should be noted that, taking the baoding-kunshan as an example of a neighboring route of beijing-shanghai, during calculation, the data of the average value of the mileage of the baoding-kunshan route obtained in step 2 may be directly utilized, so that compared with the method of obtaining the average value of the mileage of a neighboring route by other methods, processing resources and calculation time are saved.

In addition, the origin mileage difference is actually related to the origin, that is, when the neighboring origin is determined, the number is obtained, so that the destination mileage difference can be directly used, and similarly, the destination mileage difference can also be directly used. The following are exemplary: if the basic line is Beijing-Shanghai, if the adjacent line is baoding-Kunshan, the original place mileage difference between the adjacent line and the basic line can directly utilize the transport mileage average value of the baoding-Beijing basic line; similarly, the target mileage difference between the neighboring line and the basic line can directly use the average value of the mileage of Shanghai-Kunshan.

Step b 5: and obtaining the weighted mileage difference of each adjacent line according to the origin mileage difference, the destination mileage difference, the transportation mileage average difference and the weight thereof, and calculating the mileage weight coefficient of each adjacent line according to the weighted mileage difference.

Specifically, in this embodiment, the mileage weight coefficient of each neighbor line is calculated according to the following formula:

wherein DC is a mileage weight coefficient, and WD is a weighted mileage difference

WD is obtained from the origin mileage difference, the destination mileage difference, the mean transportation mileage difference, and their weights (i.e., three weights corresponding to the origin mileage difference, the destination mileage difference, and the transportation mileage difference). Wherein the sum of the three weights corresponding to the origin mileage difference, the destination mileage difference and the transportation mileage difference is equal to 1; the weight of the corresponding origin mileage difference or the corresponding destination mileage difference is larger than the weight of the corresponding transportation mileage difference; the weights for the origin mileage difference and the destination mileage difference may be equal. The following are exemplary: if yes, the corresponding origin mileage weight is 0.375; the weight corresponding to the target mileage difference is 0.375; the weight corresponding to the transport mileage difference is 0.25. Wherein, 0.375, 0.25 are the preferred values, and the three weights can be adjusted adaptively according to the above rules in practical application.

And then multiplying the origin mileage difference, the destination mileage difference and the transportation mileage difference by respective corresponding weights respectively and then summing to obtain the weighted mileage difference, namely WD.

Illustratively, if the basic line is beijing-shanghai and the neighbor line is baoding-kunshan, and the preferred values of the three weights are used, then the WD of the baoding-kunshan neighbor line is as follows:

WD ═ 0.375+ ("shanghai-shanghai" basic line transport mileage mean and "baoding-kunshan" basic line transport mileage mean) ("beijing-shanghai" basic line transport mileage mean and "baoding-kunshan" basic line transport mileage mean) ("difference) (" baoding-beijing-shanghai "basic line transport mileage mean and" baoding-kunshan "basic line transport mileage mean) (" baoding-beijing "basic line transport mileage mean and" baoding-kunshan "basic line transport mileage mean) (" baoding-beijing "basic line transport mileage mean and" baoding-kunshan "transport mileage mean)

After WD is obtained, the mileage weighting factor of the neighbor line can be obtained according to the formula for calculating DC in the foregoing.

The mileage weight coefficient of each neighbor line can be obtained according to the above steps.

Step b 6: calculating an order confidence coefficient of each neighboring line according to the historical order quantity corresponding to each neighboring line;

specifically, in this embodiment, the order confidence coefficient of each neighbor line is calculated according to the following formula:

wherein RC is order confidence coefficient, n is historical order quantity

Since each neighboring line has other corresponding basic lines, the historical orders of the other basic lines can be used, and the historical orders are obtained before and can be directly used.

Step b 7: obtaining the neighbor coefficient of each neighbor line according to the mileage weight coefficient and the order confidence coefficient of each neighbor line;

specifically, the mileage weight coefficient of each neighbor line is multiplied by the order confidence coefficient (i.e., DC × RC), so as to obtain the neighbor coefficient of the neighbor line.

Step b 8: obtaining single-kilometer quoted price of each basic line according to the neighbor coefficient of the neighbor line and the single-kilometer freight price;

specifically, the neighbor coefficients of all neighbor lines corresponding to each basic line are normalized to obtain the quotation coefficients of all neighbor lines corresponding to each basic line; and then multiplying the quotation coefficients of all the adjacent lines corresponding to each basic line by the single-kilometer freight rate of the adjacent lines, and summing to obtain the respective single-kilometer quotation of each basic line. The normalization may be to map the neighbor coefficients of all neighbor lines to a decimal number between (0,1), so that the sum of the quotation coefficients of all neighbor lines corresponding to one basic line is equal to 1.

More specifically, each basic line has its own corresponding neighboring line, and therefore, a basic line is used for illustration, neighbor coefficients of all neighboring lines corresponding to the basic line are normalized to obtain quotation coefficients of all neighboring lines, for example, the basic line 1 has 3 corresponding neighboring lines, the neighboring line 1, the neighboring line 2, the neighboring line 3, the neighboring line 1 has a neighbor coefficient of 0.7, the single-kilometer running price is 15 yuan, the neighboring line 2 has a neighbor coefficient of 0.5, the single-kilometer running price is 18 yuan, the neighboring line 3 has a neighbor coefficient of 0.8, and the single-kilometer running price is 16 yuan, so after normalization, the quotation coefficient of the neighboring line 1 is 0.35, the quotation coefficient of the neighboring line 2 is 0.25, and the quotation coefficient of the neighboring line 3 is 0.4; then, the single kilometer quoted price of the basic line is obtained only by multiplying the quoted coefficients of all the neighboring lines corresponding to the basic line by the single kilometer running price thereof and summing the quoted coefficients, that is, the single kilometer quoted price of the basic line 1 is the quoted coefficient of the neighboring line 1 is the single kilometer running price of the neighboring line 1 + the quoted coefficient of the neighboring line 2 is the single kilometer running price of the neighboring line 2 + the quoted coefficient of the neighboring line 3 is the single kilometer running price of the neighboring line 3 is 0.35 + 15+0.25 + 18+0.4 is 16.15.

Step b 9: and establishing a neighbor quotation table according to the corresponding relation between each basic line and the single-kilometer quotation.

Because each basic line can obtain the single-kilometer quotation corresponding to the basic line by the method, the relation can be utilized to establish a neighbor quotation table. For example, the abscissa of the neighbor bid table may be the base line, and the ordinate may be the single kilometer bid, or other forms of lists.

Further, another logistics order information processing method is provided in the embodiment of the present application, as shown in fig. 2, the method includes the following steps:

acquiring an origin, a destination and a transportation vehicle type uploaded by a user side;

obtaining a first mileage according to an origin and a destination;

obtaining a target basic route and a second mileage according to the origin, the destination and the vehicle type;

obtaining a corresponding relation curve from a relation curve database according to the transport vehicle type;

dividing the product of the first single-kilometer quotation and the third single-kilometer quotation by the second single-kilometer quotation to obtain a final single-kilometer quotation;

and sending the quotation to the user side, and displaying the quotation for the user by the user side.

For better understanding, the following further description is provided:

s201, acquiring an origin, a destination and a transportation vehicle type uploaded by a user side.

The server or the background system and other execution devices can acquire the relevant information of the origin, the destination and the transport vehicle type uploaded by the user through the user side.

S202, obtaining a first mileage according to an origin and a destination; obtaining a target basic route and a second mileage according to the origin, the destination and the vehicle type; and obtaining a corresponding relation curve from the relation curve database according to the transportation vehicle type.

Obtaining a first mileage according to the origin and the destination, wherein the mileage of the shortest driving path between the origin and the destination is used as the first mileage; the specific implementation process may refer to S102.

The target basic route is obtained according to the origin, the destination and the transportation vehicle type, and a target basic route may be determined according to the origin, the destination and the transportation vehicle type, and the specific implementation process may refer to S102.

Obtaining a second mileage according to the origin, the destination and the transportation vehicle type, wherein a target basic route is determined according to the origin, the destination and the transportation vehicle type, a plurality of corresponding historical orders (namely historical orders with the same origin, destination and transportation vehicle type) are obtained according to the target basic route, and the average value of the transportation mileage of the historical orders is used as the second mileage; the specific implementation process thereof may refer to S102.

Obtaining a corresponding relation curve from a relation curve database according to the transportation vehicle type, wherein the relation curve corresponding to the transportation vehicle type can be selected from the relation curve database according to the transportation vehicle type of the plurality of orders; the specific implementation process may refer to S102.

S203, obtaining a first single-kilometer quoted price according to the relation curve and the first mile; obtaining a second single-kilometer quoted price according to the relation curve and the second mileage; and obtaining a third single-kilometer quotation according to the target basic line and the neighbor quotation table.

Reference may be made to S103 for specific implementation.

S204, dividing the product of the first single-kilometer quotation and the third single-kilometer quotation by the second single-kilometer quotation to obtain a final single-kilometer quotation; the product of the final single-kilometer quote and the first mile is taken as the quote.

The specific implementation process may refer to S104.

S205, sending the quotation to the user side, and displaying the quotation for the user by the user side.

As can be seen from the above description, in the embodiment of the present application, the transportation quote can be directly provided for the user according to the origin, the destination and the transportation vehicle type issued by the user, and no matter the user is the user who issues the order or the user who intends to pick up the order, as long as the user proposes the quote demand, the system can give the transportation quote, and the user is prevented from issuing the order for the same transportation demand multiple times.

Finally, beneficial effects of the transportation order processing method based on the neighbor quotation table are summarized:

1. the system can directly provide quotation for the user, and the system can provide quotation as long as the user puts forward a quotation demand no matter the user is the user who releases the order or the user who intends to receive the order, so that the user is prevented from releasing the order for the same transportation demand for many times;

2. the method has the advantages that the method can cancel the issuance of other orders and reduce resource consumption by judging whether a user issues a plurality of orders with different prices for the same transportation demand and not finding out the order which is closest to the quoted price, and in addition, the issuance state of the order which is closest to the price of the order is kept because the quoted value is the price fixed value which is closest to the order, so that the method can balance the market order and the order transaction speed and improve the user experience;

3. the quote can provide more accurate quote even aiming at the condition that the historical orders on the transportation line are few or no.

It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than here. The description of the relevant contents in the above embodiments may be referred to each other.

According to an embodiment of the present application, there is also provided a logistics order information processing apparatus for implementing the method shown in fig. 1, as shown in fig. 3, the apparatus includes:

the order obtaining module 31 is configured to obtain a plurality of orders with the same origin, destination, transportation vehicle type, and delivery time among the orders currently issued by the same user.

A mileage determining module 32 for obtaining a first mileage based on the origin and destination of the plurality of orders; obtaining a target basic route and a second mileage according to the origin, the destination and the transportation vehicle type of the orders; and obtaining a corresponding relation curve from a relation curve database according to the transportation vehicle types of the orders.

A single-kilometer quotation determining module 33, configured to obtain a first single-kilometer quotation according to the relationship curve and the first mileage; obtaining a second single-kilometer quoted price according to the relation curve and the second mileage; and obtaining a third single-kilometer quotation according to the target basic line and the neighbor quotation table.

A quote determining module 34, configured to divide a product of the first single-kilometer quote and the third single-kilometer quote by the second single-kilometer quote to obtain a final single-kilometer quote; and taking the product of the final single-kilometer quote and the first mile as a quote.

The order processing module 35 is configured to reserve one of the orders with the closest order price to the quoted price, and cancel the release of the other orders.

Further, the apparatus further comprises:

and a relation curve database establishing module 36, configured to establish a relation curve database according to the transportation mileage, the single-kilometer transportation price, and the transportation vehicle type in the historical order.

Further, the relational database building module 36 includes:

the determining unit 361 is used for determining the mileage characteristics and the single-kilometer freight rate in each data set according to the transport mileage data, the single-kilometer freight rate data and the transport vehicle type data in the historical orders, wherein each data set corresponds to one group, and different groups correspond to different transport vehicle types;

a fitting unit 362, configured to fit the mileage characteristics and the single-kilometer freight rate in each data set by using a regression algorithm, so as to obtain a relationship curve between the transportation mileage and the single-kilometer freight rate in each group;

the database establishing unit 363 is configured to establish a relational curve database by using a corresponding relationship between the transportation vehicle type data and the relational curve.

Further, the apparatus further comprises:

and a neighbor quotation table establishing module 37, configured to establish a neighbor quotation table according to the origin, the destination, the transportation vehicle type, the neighbor lines of the transportation line, and the single-kilometer freight rates of the neighbor lines in the historical order.

Further, the neighbor bid table creating module 37 includes:

a basic route determining unit 371, configured to obtain a plurality of historical orders, group the plurality of historical orders according to the origin and destination of each route in the road transportation route table and in combination with transportation vehicle types, where each group corresponds to one basic route;

a basic line data determining unit 372, configured to determine, according to the historical orders in each group, the number of orders, the average transportation mileage and the single kilometer freight rate corresponding to each basic line;

a neighbor line determining unit 373 that determines all neighbor lines corresponding to each basic line based on the origin and destination of the basic line;

a mileage weight coefficient determining unit 374, configured to calculate a mean difference of transportation mileage, an originating mileage difference, and a destination mileage difference between each neighboring line and its corresponding basic line; obtaining a weighted mileage difference of each adjacent line according to the origin mileage difference, the destination mileage difference, the transportation mileage average difference and the weight thereof, and calculating a mileage weight coefficient of each adjacent line according to the weighted mileage difference;

a confidence coefficient determining unit 375, configured to calculate an order confidence coefficient of each neighboring line according to the historical order number corresponding to each neighboring line;

a neighbor coefficient determining unit 376, configured to obtain a neighbor coefficient of each neighbor line according to the mileage weight coefficient and the order confidence coefficient of each neighbor line;

a single-kilometer quotation determining unit 377 configured to obtain a single-kilometer quotation of each basic line according to the nearest neighbor coefficient of the nearest neighbor line and the single-kilometer freight rate;

a quotation table establishing unit 378, configured to establish a neighboring quotation table according to a correspondence between each basic line and its single-kilometer quotation.

According to an embodiment of the present application, there is also provided a logistics order information processing apparatus for implementing the method shown in fig. 2, as shown in fig. 4, the apparatus includes:

the obtaining module 41 is configured to obtain an origin, a destination, and a transportation vehicle type uploaded by a user side;

a mileage module 42 for obtaining a first mileage based on the origin and the destination; obtaining a target basic route and a second mileage according to the origin, the destination and the vehicle type; obtaining a corresponding relation curve from a relation curve database according to the type of the transportation vehicle;

a freight rate module 43, configured to obtain a first single-kilometer quote according to the relationship curve and the first mileage; obtaining a second single-kilometer quoted price according to the relation curve and the second mileage; obtaining a third single-kilometer quotation according to the target basic line and the neighbor quotation table;

a quotation module 44, configured to obtain a final single-kilometer quotation by dividing a product of the first single-kilometer quotation and the third single-kilometer quotation by the second single-kilometer quotation; taking the product of the final single-kilometer quoted price and the first mile as a quoted price;

and the display module 45 is used for sending the quotation to the user side, and the user side displays the quotation for the user.

Specifically, the specific process of implementing the functions of each unit and module in the device in the embodiment of the present application may refer to the related description in the method embodiment, and is not described herein again.

There is further provided a computer-readable storage medium according to an embodiment of the present application, where the computer-readable storage medium stores computer instructions for causing the computer to execute the transportation order processing method based on the neighbor quotation table in the above method embodiment.

According to an embodiment of the present application, there is also provided an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores a computer program executable by the at least one processor to cause the at least one processor to perform a method of neighboring-quote-table-based transportation order processing in the above-described method embodiments.

It will be apparent to those skilled in the art that the modules or steps of the present application described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and they may alternatively be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, or fabricated separately as individual integrated circuit modules, or fabricated as a single integrated circuit module from multiple modules or steps. Thus, the present application is not limited to any specific combination of hardware and software.

The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for processing logistics order information, wherein the method comprises:

Get multiple orders with the same origin, destination, transportation model, and delivery time among the orders currently published by the same user;

obtain the first mileage according to the origin and destination of the plurality of orders;

Obtain the target basic route and the second mileage according to the origin, destination and transportation type of the multiple orders;

Obtaining a corresponding relationship curve from the relationship curve database according to the transportation models of the multiple orders;

According to the relationship curve and the first mileage, get the quotation for the first single kilometer;

According to the relationship curve and the second mileage, get the quotation for the second single kilometer;

Obtain the quotation for the third kilometer according to the target basic route and the quotation table of the nearest neighbors;

Divide the product of the quotation for the first kilometer and the quotation for the third kilometer by the quotation for the second kilometer to get the final quotation per kilometer;

Take the product of the final single kilometer quotation and the first mileage as the quotation;

One of the multiple orders whose price is closest to the quoted price is reserved, and the release of other orders is canceled.

2. The method for processing logistics order information according to claim 1, wherein the method further comprises:

According to the origin, destination, transportation type, neighboring lines of transportation lines, and single-kilometer freight rates of neighboring lines in historical orders, a neighboring quotation table is established.

3. The method for processing logistics order information according to claim 2, characterized in that, said establishment according to the origin, destination, transportation vehicle type, adjacent routes of transportation routes, and single-kilometer freight rates of adjacent routes in historical orders The Neighbor Quote Table includes:

Obtain multiple historical orders, group multiple historical orders according to the origin and destination of each line in the road transport route table, and combine the transport models, and each group corresponds to a basic line;

According to the historical orders in each group, determine the number of orders, the average transportation mileage and the single-kilometer freight rate corresponding to each basic line;

Determine all the neighboring lines corresponding to each basic line according to the transportation type, origin and destination of the basic line;

Calculate the mean difference of transportation mileage, the difference of origin mileage and the difference of destination mileage between each neighboring line and its corresponding basic line;

Obtain the weighted mileage difference of each neighboring line according to the origin mileage difference, the destination mileage difference, the average difference of transportation mileage and its weight, and calculate the mileage weight coefficient of each neighboring line according to the weighted mileage difference;

Calculate the order confidence coefficient of each neighboring line according to the number of historical orders corresponding to each neighboring line;

According to the mileage weight coefficient of each neighboring line and the order confidence coefficient, the neighboring coefficient of each neighboring line is obtained;

Obtain the single-kilometer quotation of each basic line according to the neighboring coefficient of the neighboring line and the single-kilometer freight rate;

According to the corresponding relationship between each basic line and its single-kilometer quotation, a neighbor quotation table is established.

4. The logistics order information processing method according to claim 1, wherein the method further comprises:

A relational curve database is established based on the transportation mileage, single-kilometer freight rate, and transportation models in historical orders.

5. The method for processing logistics order information according to claim 4, wherein the establishing a relational curve database according to the transportation mileage, the single-kilometer freight rate, and the transportation vehicle type in the historical order comprises:

According to the transportation mileage data, single-kilometer freight rate data, and transportation model data in the historical orders, determine the mileage characteristics and single-kilometer freight rate in each data set, each data set corresponds to a group, and different groups correspond to different transportation models;

Use regression algorithm to fit the mileage characteristics and single-kilometer freight rate in each data set, and obtain the relationship curve between transportation mileage and single-kilometer freight rate in each group;

The relational curve database is established by using the correspondence between the transport vehicle data and the relational curve.

6. A method for processing logistics order information, the method comprising:

Obtain the origin, destination and transport model uploaded by the client;

Get the first mile based on the origin and destination;

Obtain the target basic route and second mileage according to the origin, destination and transportation model;

Obtain the corresponding relationship curve from the relationship curve database according to the transport model;

According to the product of the quotation of the first single kilometer and the quotation of the third single kilometer divided by the quotation of the second single kilometer, the final single kilometer quotation is obtained;

Send the quotation to the client, and the client displays the quotation for the user.

7. A logistics order information processing device, wherein the device comprises:

The order acquisition module is used to acquire multiple orders with the same origin, destination, transportation model and delivery time among the orders currently issued by the same user;

a mileage determination module, configured to obtain the first mileage according to the origin and destination of the multiple orders; obtain the target basic route and the second mileage according to the origin, destination and transportation type of the multiple orders; Obtaining the corresponding relationship curves from the relationship curve database for the transportation models of the multiple orders;

The single-kilometer quotation determination module is used to obtain the first single-kilometer quotation according to the relationship curve and the first mileage; obtain the second single-kilometer quotation according to the relationship curve and the second mileage; obtain the third single-kilometer quotation according to the target basic route and the neighboring quotation table ;

The quotation determination module is used to divide the product of the quotation of the first single kilometer and the quotation of the third single kilometer by the quotation of the second single kilometer to obtain the final quotation per kilometer; the product of the quotation of the final single kilometer and the first mileage is used as the quotation;

The order processing module is used for retaining an order whose order price is closest to the quotation among the multiple orders, and canceling the release of other orders.

8. A logistics order information processing device, wherein the device comprises:

The acquisition module is used to acquire the origin, destination and transport model uploaded by the client;

The mileage module is used to obtain the first mileage according to the origin and destination; obtain the target basic route and the second mileage according to the origin, destination and transport model; obtain the corresponding relationship curve from the relationship curve database according to the transport model;

The freight module is used to obtain the quotation of the first single kilometer according to the relationship curve and the first mileage; obtain the quotation of the second single kilometer according to the relationship curve and the second mileage; obtain the quotation of the third single kilometer according to the target basic line and the neighboring quotation table;

The quotation module is used to obtain the final quotation per kilometer after dividing the product of the quotation of the first kilometer and the quotation of the third kilometer by the quotation of the second kilometer; the product of the quotation of the final kilometer and the first mileage is used as the quotation;

The display module is used to send the quotation to the client, and the client displays the quotation for the user.

9. A computer-readable storage medium, characterized in that the computer-readable storage medium stores computer instructions, the computer instructions are used to cause the computer to execute the system based on any one of claims 1 to 6. Shipping order processing method for the Neighbor Quote table.

10. An electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor , the computer program is executed by the at least one processor, so that the at least one processor executes the transportation order processing method based on the neighbor quotation table according to any one of claims 1 to 6.