CN113762815B

CN113762815B - Logistics distribution information processing method, device, equipment and storage medium

Info

Publication number: CN113762815B
Application number: CN202010506570.3A
Authority: CN
Inventors: 熊资; 阮思捷; 鲍捷; 郑宇�
Original assignee: Jingdong City Beijing Digital Technology Co Ltd
Current assignee: Jingdong City Beijing Digital Technology Co Ltd
Priority date: 2020-06-05
Filing date: 2020-06-05
Publication date: 2024-10-22
Anticipated expiration: 2040-06-05
Also published as: CN113762815A

Abstract

The embodiment of the invention provides a processing method, a device, equipment and a storage medium of logistics distribution information, wherein order distribution information and distribution track data are acquired, a target order set with accurate time for throwing is determined according to the order distribution information and the distribution track data, and finally a distribution time window of a target residence point in a target distribution period is determined according to the target order set and preset constraint conditions. According to the technical scheme, on the basis of the acquired order distribution information, the order with accurate delivery time is determined by combining the distribution track data, and then the distribution time window of a certain target residence point in the target distribution time period can be accurately determined by combining the preset constraint conditions, so that the goods distribution is performed based on the accurate distribution time window, and the distribution efficiency of the goods is improved.

Description

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

Technical Field

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

Background

With the rapid growth of economy and the rapid development of the internet industry, people begin to make online shopping more and more. In the business scenario of the e-commerce logistics distribution, improving the distribution efficiency is a key factor for improving the shopping experience of users and reducing the logistics cost, and determining the time and place where the users can receive the express delivery for improving the distribution efficiency is key.

In the prior art, the delivery time of the to-be-delivered goods is determined mainly according to the first historical delivery record information of the to-be-delivered goods at the delivery station and the second historical delivery record information determined by the to-be-delivered goods corresponding to the delivery staff, namely, the time required between the starting delivery of the to-be-delivered goods and the delivery of the to-be-delivered goods is calculated from the delivery station, and the delivery time of the to-be-delivered goods on the same day is determined by combining the starting delivery time point of the to-be-delivered goods, so that the accurate goods delivery time is determined.

However, in the logistics distribution service scenario, when the actual distribution time of each to-be-distributed goods is online, the actual distribution time of each goods needs to be recorded by clicking the confirmation time of the goods in the system by the distributor, and the distributor sometimes delays confirmation time due to condition limitation and other reasons, so that the acquired second historical distribution record information is inaccurate, and therefore, the problem of low accuracy of the goods distribution time determined by the prior art exists.

Disclosure of Invention

The embodiment of the application provides a processing method, a device, equipment and a storage medium of logistics distribution information, which are used for solving the problem of low accuracy of goods distribution time determined by the prior art.

In a first aspect, an embodiment of the present application provides a method for processing logistics distribution information, including:

acquiring order distribution information and distribution track data;

determining a target order set with accurate time for putting the order according to the order distribution information and the distribution track data;

and determining a delivery time window of the target residence point in the target delivery period according to the target order set and the preset constraint condition.

In one possible design of the first aspect, the determining, according to the target order set and the preset constraint condition, a delivery time window of the target residence point in the target delivery period includes:

determining at least one target residence point according to the receiving address information of each order in the target order set;

For each target resident point, determining at least one target delivery period of the target resident point according to a preset throwing time threshold and preset delivery time;

for each target delivery period of each target residence point, determining the number of times of the time slot in each time slot included in the target delivery period according to a preset time granularity;

normalizing the number of times of the toboggan in each time period included in the target delivery period to obtain probability distribution of the number of times of the toboggan in the target delivery period;

and determining a delivery time window of the target residence point in the target delivery period according to the probability distribution of the number of times of delivery in the target delivery period, a preset order total delivery value and a preset time window threshold.

In another possible design of the first aspect, the determining a target order set with accurate time for putting the order according to the order distribution information and the distribution track data includes:

Determining all residence points in the distribution track data according to a preset track point distance threshold and a preset time interval threshold;

according to the order distribution information, receiving address information, receiving time and distribution time of each order are determined;

determining a candidate resident point set of each order according to the receiving address information, the receiving time and the delivery time of each order, wherein the candidate resident point set comprises at least one resident point;

Determining a target order set according to the candidate resident point set of each order and the delivery time of the order, wherein the target order comprises: an order with accurate actual time and an order with corrected time.

In this possible design of the first aspect, the determining the target set of orders according to the candidate set of points for each order and the delivery time of the order includes:

determining an intermediate time stamp of each resident point according to the start-stop time of each resident point in the candidate resident point set corresponding to each order;

Determining an order with accurate actual time and an order with delayed actual time according to the intermediate time stamp of the resident point in the candidate resident point set corresponding to each order, the delivery time of the order and a preset time threshold;

And processing the actual order with the time delay according to the number of the resident points in the candidate resident point set corresponding to the actual order with the time delay and/or the intermediate time stamp of the resident points, so as to obtain an order with the corrected time delay.

Optionally, the determining an order with accurate actual time and an order with delayed actual time according to the intermediate time stamp of the resident point in the candidate resident point set corresponding to each order, the delivery time of the order, and a preset time threshold includes:

if the middle time stamp of at least one resident point exists in the candidate resident point set corresponding to each order and the delivery time of the order meet a preset time threshold, determining that the order is an order with accurate actual time;

if the intermediate time stamp of all the resident points in the candidate resident point set corresponding to each order and the delivery time of the order do not meet a preset time threshold, determining that the order is an order with actual time delay.

In this possible design of the first aspect, the processing the actual delayed order according to the number of residence points and/or intermediate timestamps of residence points in the candidate residence point set corresponding to the actual delayed order to obtain a corrected order after the time delay includes:

For an order with actual time delay, if the resident point set corresponding to the order comprises at least two resident points, rejecting the order;

And if the resident point set corresponding to the order only comprises 1 resident point, correcting the delivery time of the order to be the middle timestamp of the resident point, and obtaining the order with corrected time.

In yet another possible design of the first aspect, before the determining the target order set with accurate time for delivery based on the order delivery information and the delivery trajectory data, the method further includes:

And removing noise points in the distribution track data according to a preset speed threshold and the distance and time between two continuous track points in the distribution track data to obtain updated distribution track data.

In a second aspect, an embodiment of the present application provides a processing apparatus for logistics distribution information, including: the device comprises an acquisition module, a first processing module and a second processing module;

The acquisition module is used for acquiring order distribution information and distribution track data;

the first processing module is used for determining a target order set with accurate time for putting the order according to the order distribution information and the distribution track data;

and the second processing module is used for determining a delivery time window of the target residence point in the target delivery period according to the target order set and the preset constraint condition.

In one possible design of the second aspect, the second processing module is specifically configured to:

In another possible design of the second aspect, the first processing module is specifically configured to:

In this possible design of the second aspect, the first processing module is configured to determine the target order set according to a candidate residence point set of each order and a delivery time of the order, specifically:

The first processing module is specifically configured to:

Optionally, the first processing module is configured to determine, according to an intermediate timestamp of a resident point in the candidate resident point set corresponding to each order, a delivery time of the order, and a preset time threshold, an order with accurate actual time and an order with delayed actual time, where the order is specifically:

The first processing module is specifically configured to determine that the order is an order with accurate actual time when an intermediate timestamp of at least one resident point exists in each candidate resident point set corresponding to the order and the delivery time of the order meet a preset time threshold, and determine that the order is an order with delayed actual time when the intermediate timestamps of all resident points in each candidate resident point set corresponding to the order and the delivery time of the order do not meet the preset time threshold.

In this possible design of the second aspect, the first processing module is configured to process the actual order with the time delay to obtain an order with corrected time delay according to the number of residence points and/or intermediate timestamps of residence points in the candidate residence point set corresponding to the actual order with the time delay, where the order with corrected time delay is specifically:

the first processing module is specifically configured to reject an order with delayed actual time, if the resident point set corresponding to the order includes at least two resident points, and correct the delivery time of the order to be a timestamp of the resident point when the resident point set corresponding to the order includes only 1 resident point, so as to obtain an order with corrected time.

In still another possible design of the second aspect, the first processing module is further configured to, before determining, according to the order delivery information and the delivery track data, a target order set with accurate delivery time, remove noise points in the delivery track data according to a preset speed threshold and a distance and time between two consecutive track points in the delivery track data, and obtain updated delivery track data.

The apparatus provided in the second aspect of the present application may be used to perform the method provided in the first aspect, and its implementation principle and technical effects are similar, and are not described herein again.

In a third aspect, an embodiment of the present application further provides an electronic device, including a processor, a memory, and a computer program stored on the memory and executable on the processor, where the processor executes the program to implement the method according to the first aspect and each possible design.

In a fourth aspect, embodiments of the present application also provide a computer-readable storage medium having stored therein computer instructions which, when run on a computer, cause the computer to perform the method of the first aspect and each possible design.

According to the logistics distribution information processing method, device, equipment and storage medium, the order distribution information and distribution track data are obtained, the target order set with accurate time is determined according to the order distribution information and the distribution track data, and finally the distribution time window of the target residence point in the target distribution period is determined according to the target order set and preset constraint conditions. According to the technical scheme, on the basis of the acquired order distribution information, the order with accurate delivery time is determined by combining the distribution track data, and then the distribution time window of a certain target residence point in the target distribution time period can be accurately determined by combining the preset constraint conditions, so that the goods distribution is performed based on the accurate distribution time window, and the distribution efficiency of the goods is improved.

Drawings

Fig. 1 is an application scenario schematic diagram of a method for processing physical distribution information according to an embodiment of the present application;

Fig. 2 is a schematic flow chart of a first embodiment of a method for processing logistics distribution information provided by the present application;

Fig. 3 is a schematic flow chart of a second embodiment of a method for processing logistics distribution information provided by the present application;

FIG. 4 is a schematic diagram of probability distribution of the number of trails according to an embodiment of the present application;

FIG. 5 is a diagram illustrating determining a delivery time window based on a probability distribution of the number of times of the delivery and a predetermined time window threshold in an embodiment of the present application;

fig. 6 is a schematic flow chart of a third embodiment of a method for processing logistics distribution information provided by the present application;

Fig. 7 is a schematic flow chart of a fourth embodiment of a method for processing logistics distribution information provided by the present application;

FIG. 8 is a block diagram of a fifth embodiment of a method for processing logistics distribution information provided by the present application;

fig. 9 is a schematic structural diagram of an embodiment of a processing device for logistics distribution information provided by the present application;

Fig. 10 is a schematic structural diagram of an electronic device for executing the processing method of logistics distribution information.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

With the rapid growth of economy and the rapid development of the Internet industry, people begin to make online shopping more and more, and network technology and electronic commerce rapidly develop, so that the logistics distribution industry rapidly develops. The logistics distribution is a circulation mode of goods seen from circulation operation mode of goods. The logistics distribution can provide service for clients of electronic commerce, and according to the characteristics of the electronic commerce, unified information management and scheduling are carried out on the whole logistics distribution system, and according to the ordering requirements of users, the logistics distribution system carries out the goods management work on a logistics base and delivers the distributed goods to a delivery person.

In the physical distribution industry, particularly in the e-commerce logistics express service scene, distribution efficiency is an important problem, and how to improve the distribution efficiency of goods is a key to reduce logistics distribution cost. In the scheme for improving the delivery efficiency, the time window of the user is mined, namely, the time and the place where the user can receive the express delivery are determined, which is important for the subsequent delivery path planning.

In the prior art, simple statistics are mainly performed based on data (first historical delivery record information of a delivery station where the goods to be delivered are located and second historical delivery record information determined by a corresponding delivery person of the goods to be delivered) in a warehouse of a logistics system, which has unrealistically high requirements on quality of the logistics data, for example, all delivery persons are required to accurately record delivery time of each order. However, in an actual logistics distribution service scenario, the actual distribution and delivery actions occur on line, the time of the actual distribution and delivery actions cannot be directly put into storage, the actual distribution and delivery actions can be recorded only by clicking and confirming the actual distribution and delivery actions in the system, and the actual distribution and delivery actions can be delayed and confirmed by the distributor due to condition limitation and other reasons, so that the data put into storage of the logistics system is inaccurate, and the accuracy of the goods distribution time determined in the existing scheme is low.

In view of the above problems, an embodiment of the present application provides a method for processing logistics distribution information, by acquiring order distribution information and distribution track data, determining a target order set with accurate time for delivery according to the order distribution information and the distribution track data, and finally determining a distribution time window of a target residence point in a target distribution period according to the target order set and a preset constraint condition. According to the technical scheme, on the basis of the acquired order distribution information, the order with accurate delivery time is determined by combining the distribution track data, and then the distribution time window of a certain target residence point in the target distribution time period can be accurately determined by combining the preset constraint conditions, so that the goods distribution is performed based on the accurate distribution time window, and the distribution efficiency of the goods is improved.

The technical conception of the technical scheme of the application is as follows: the reason for low accuracy of the delivery time window in the logistics delivery scene is mainly that delivery time manually recorded by a delivery person in a logistics system is inaccurate, and the reason for low availability of the delivery time window is that the set time window limits parameters such as the length of the time window, and the flexibility is poor. In the embodiment of the application, aiming at an actual service scene, technologies such as track data mining and the like are used, and according to the distribution track data of orders recorded by the GPS equipment carried by a distributor, and the logistics and electronic commerce orders (order information) are combined, the accurate distribution time can be determined, namely, a distribution time window with interpretability and usability is obtained, so that data support is provided for optimization of a distribution path.

Before introducing the technical scheme of the application, an application scene of the embodiment of the application is first introduced.

Fig. 1 is a schematic application scenario diagram of a method for processing physical distribution information according to an embodiment of the present application. Referring to fig. 1, the application scenario may include: a distribution station, a plurality of residence points, and electronics (not shown).

The distribution station may also be referred to as a distribution center, and may be used to refer to a logistics node, i.e. a distribution station, of a logistics or express company in each area. Typically, the site is the smallest distribution site of a logistics or express company, and when the goods arrive at the distribution site, the goods will be distributed to the distribution staff in the corresponding area, and then the distribution staff distributes the goods.

In an embodiment of the application, the point of residence may be determined based on the shipping addresses in the order information, and the shipping addresses for the multiple orders may correspond to the same point of residence. The embodiment of the application does not limit the specific relation between the residence point and the order information.

The electronic equipment can acquire order delivery information stored in the logistics system and delivery track data recorded by a delivery person, further analyze and process the order delivery information and the delivery track data, determine a target order set with accurate time for delivery, and determine a delivery time window of the target residence point in the target delivery period by combining preset constraint conditions in the electronic equipment.

Further, after the electronic device determines the delivery time window of the target residence point in the target delivery period, the electronic device can push the delivery time window of the target residence point in the target delivery period to the delivery person, so that the delivery person knows the delivery time window of the target residence point in the target delivery period, and a reference basis is provided for the delivery time of the delivery person, so that the delivery time of goods can be improved, and the delivery efficiency is further improved.

For example, if the electronic device is implemented by the server, after the electronic device determines the delivery time window of the target residence point in the target delivery period, the delivery time window of the target residence point in the target delivery period may be pushed to the terminal device, so that the terminal device presents the delivery time window to the dispatcher; if the electronic device is implemented by the terminal device, the electronic device may directly present the target residence point to the dispatcher after determining the delivery time window of the target residence point in the target delivery period.

It may be appreciated that the embodiment of the present application is not limited to a specific implementation scheme in which the electronic device pushes, to the dispatcher, the delivery time window of the target residence point in the target delivery period, which may be determined according to actual requirements, and will not be described herein.

The application scenario shown in fig. 1 includes 1 distribution station and 6 residence points, where the triangle shape represents a distribution center, the circle real point represents a residence point, and the abscissa is a longitude value and the ordinate is a latitude value. According to the technical scheme of the application, the electronic equipment can respectively determine the distribution time window of each residence point in the target distribution period.

It may be understood that the execution body of the embodiment of the present application may be an electronic device, for example, a terminal device such as a computer, a tablet computer, or the like, or may be a server, for example, a background processing platform, or the like. Thus, the present embodiment is explained by collectively referring to the terminal device and the server as an electronic device, and it is possible to determine whether the electronic device is specifically a terminal device or a server.

The technical scheme of the application is described in detail through specific embodiments. It should be noted that the following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

Fig. 2 is a schematic flow chart of an embodiment of a method for processing logistics distribution information. As shown in fig. 2, the method may include the steps of:

s201, order distribution information and distribution track data are acquired.

The order delivery information may include delivery information of each order, such as, for example, order recipient address information, recipient information, and the like. The delivery trajectory data is primarily the movement trajectory of the delivery person or the delivery device, which is used to characterize the position information experienced by the delivery person during delivery. By way of example, the delivery trajectory data may refer to trajectory data generated by a handheld terminal (PDA) carried by a logistics dispenser.

In the embodiment of the present application, the order distribution information and the distribution track information may be stored in the logistics system, so when a path planning needs to be performed on a certain area, an optimal distribution time window of a residence point included in the area may be first analyzed, and at this time, the electronic device may acquire the order distribution information and the generated distribution track data of the area from the logistics system.

S202, determining a target order set with accurate time for the delivery according to the order delivery information and the delivery track data.

In the embodiment of the application, the electronic device can perform residence point detection based on the acquired distribution track data, so as to determine a smaller area where the distribution personnel or the distribution device stays in a certain time period. The actual consignment of the dispatcher to deliver the goods to the user can be mined through the stay point detection.

The electronic equipment can determine the information such as the receiving address information, the receiving time, the delivery time and the like of each order according to the order delivery information, and further determine all orders with accurate delivery time, namely the target order set by combining the residence point determined by the delivery track data and the residence time of each residence point.

It will be appreciated that in embodiments of the present application, all orders with accurate time may include only the actual order with accurate time, or may include both the actual order with accurate time and the actual order with delayed time but corrected. The embodiment of the application is not limited to the specific composition of all orders with accurate time, and can be determined according to the situation.

For a specific implementation of this step, see the description in the embodiment shown in fig. 4 below, and will not be repeated here.

S203, determining a delivery time window of the target residence point in the target delivery period according to the target order set and the preset constraint condition.

For example, in embodiments of the present application, after an order with accurate time to fill is obtained, the optimal delivery time period for each dwell point at each target delivery time period may be counted. Illustratively, this optimal delivery period is also referred to as a delivery time window.

In the embodiment of the application, the target residence point refers to a certain receiving address, and the target delivery period refers to any one of delivery periods of morning, afternoon, morning, afternoon and the like of a working day. The delivery time window of the target residence point in the target delivery time period refers to the optimal delivery time period of the target receiving address in delivery time periods such as the morning of the working day or the afternoon of the working day or the morning of the holiday or the afternoon of the holiday.

In practical application, for the problem of optimizing the logistics distribution path, the electronic device is preconfigured with preset constraint conditions for the distribution time window, and the preset constraint conditions are formulated according to the actual operation of a distributor in an actual scene.

Alternatively, the preset constraint condition of the delivery time window may include the following:

1. in practice, for a receiving address (residence point), since the dispatcher will dispatch once in the morning and afternoon each residence point has a delivery time window (corresponding to different delivery times) in the morning and afternoon. In addition, since there is a significant difference in the time of the receivables of most recipients on weekdays (e.g., in the week) and on holidays (e.g., on weekends, weekdays, etc. and holidays), the delivery time window of each receiving address on weekdays and on holidays is calculated, respectively. Therefore, for each receiving address, the delivery time window refers to one of delivery time periods of morning, afternoon, morning on holiday, afternoon on holiday, and the like;

2. the distribution time window needs to be determined according to sufficient historical order distribution information and historical distribution track data, so that the determined distribution time window can be ensured to have statistical significance;

3. For a receiving address, the determined delivery time window needs to cover most of orders of delivery times (morning and/or afternoon of working days and/or holidays) to which the time window belongs, namely, the ratio of the amount of orders which can be properly delivered in the delivery time window to the amount of all orders in all orders delivered to the receiving address needs to be larger than a preset threshold;

4. the duration of the delivery time windows needs to be less than a duration threshold, i.e. each delivery time window is not too long, otherwise it is considered that there is no significant time window in the corresponding delivery period.

Thus, in an embodiment of the present application, the electronic device may determine the delivery time window of the target residence point (target receiving address) in the target delivery period based on the determined target order set with accurate time and the preset constraint condition.

For a specific implementation of this step, see the description in the embodiment shown in fig. 3 below, and will not be repeated here.

According to the logistics distribution information processing method, the order distribution information and the distribution track data are obtained, a target order set with accurate time for throwing is determined according to the order distribution information and the distribution track data, and finally, a distribution time window of a target residence point in a target distribution period is determined according to the target order set and preset constraint conditions. According to the technical scheme, the order with accurate delivery time is determined by using the acquired order delivery information and delivery track data, and then the delivery time window of a certain target residence point in a target delivery period can be accurately determined by combining the preset constraint conditions, and the goods delivery is performed based on the accurate delivery time window, so that the delivery efficiency of the goods is improved.

Based on the above embodiments, fig. 3 is a schematic flow chart of a second embodiment of a method for processing logistics distribution information according to the present application. In the embodiment of the present application, the step S203 may be implemented by:

s301, determining at least one target resident point according to the receiving address information of each order in the target order set.

In the embodiment of the application, the electronic equipment determines the receiving address information of each order by analyzing each order included in the target order set. Since the shipping address information for different orders may be substantially the same, e.g., the same residential area, the same office area, etc. Thus, substantially the same shipping address for multiple orders may be referred to as a target point of residence.

Optionally, the electronic device may determine at least one target residence point corresponding to all orders included in the target order set by performing statistical analysis on the receiving address information of each order in the target order set and dividing residence points based on the receiving addresses.

S302, for each target resident point, determining at least one target delivery period of the target resident point according to a preset threshold of times of throwing and preset delivery time.

In the embodiment of the application, the electronic device can determine that each target residence point can comprise four different delivery time periods according to the preset constraint condition of the delivery time window, wherein the delivery time periods are respectively workday morning, workday afternoon, holiday morning and holiday afternoon.

Therefore, the electronic device may determine the delivery period corresponding to the order based on the receiving time and the preset delivery time of the order, and further determine whether the number of times of the delivery period is greater than the threshold of times of the delivery according to the delivery periods corresponding to all orders and the preset threshold of times of the delivery, if so, determine the delivery period as a target delivery period of the target residence point.

In practical applications, the daily dispensing periods may be separated based on preset separation time points, for example, 15:30 a day as a separation time point of the morning and afternoon of the day, etc. It will be appreciated that the preset separation time point is specifically determined by the distribution schedule of the logistics company, and the embodiment of the present application is not limited thereto.

In the embodiment of the application, a preset threshold of the number of times of the toboggan is set to distinguish whether the delivery period is a target delivery period for determining the delivery time window. If the number of times of the priming in a certain delivery period is smaller than a preset threshold value of the number of times of the priming, the excavated delivery time window is considered to have no statistical significance, and therefore the delivery period does not belong to the target delivery period.

Alternatively, in practical applications, the preset threshold number of times of priming may be 20. It will be appreciated that the predetermined threshold number of times of priming may be other values, which are not limited herein.

S303, for each target delivery period of each target residence point, determining the number of times of the toboggan in each time period included in the target delivery period according to the preset time granularity.

In the embodiment of the present application, for each target delivery period of each target residence point determined above, in order to accurately determine the number of times of closing in each time period, a preset time granularity is set, so that in the calculation process, the electronic device may count the number of times of closing in all time periods included in the target delivery period with the preset time granularity as a unit.

For example, in practical applications, the preset time granularity may be minutes, i.e., for a target residence, the electronic device may count the number of jolts that occur per minute in each target delivery period.

S304, normalizing the number of times of the toboggan in each time period included in the target delivery period to obtain the probability distribution of the number of times of the toboggan in the target delivery period.

In the embodiment of the present application, after the electronic device counts the number of times of the tutor in each time period included in each target delivery period of each target residence point, the number of times of the tutor in each time period included in each target delivery period may be converted to between 0 and 1 through normalization processing, and the converted number of times of the tutor corresponding to all time periods in the target delivery period may be continuously processed, so that the probability distribution of the number of times of the tutor in the target delivery period may be obtained.

For example, when the electronic device counts the number of times of the priming in each target delivery period, the number of times of the priming in each minute can be unified to be between 0 and 1 through normalization processing, so as to obtain the probability distribution of the number of times of the priming in the target delivery period.

Further, in the embodiment of the present application, the electronic device may further perform a smoothing process on the probability distribution of the number of times of the trails based on a time window, for example, a sliding time window with W minutes as a sliding time window, and perform a sliding average process on the probability distribution of the number of times of the trails, so as to obtain a smoothed probability distribution curve of the number of times of the trails.

By way of example, the W may be 10. It can be understood that the embodiment of the present application is not limited to the specific value of W, and may be set according to actual requirements.

Fig. 4 is a schematic diagram illustrating probability distribution of the number of trails according to an embodiment of the present application. Referring to fig. 4, a thin solid line is a probability distribution curve of the number of times of the toboggan of a certain target resident point in a certain target delivery period, the horizontal axis thereof represents time in minutes, the starting point thereof represents the start time of the target delivery period in 0 minutes, the ending time thereof represents 1400 minutes, and the vertical axis thereof represents the number of times of the toboggan after normalization processing, and the value thereof is between 0 and 1, for example, 0 to 0.8.

S305, determining a delivery time window of the target residence point in the target delivery period according to the probability distribution of the number of times of delivery in the target delivery period, the preset order total delivery value and the preset time window threshold.

In the embodiment of the application, after obtaining the probability distribution of the number of times of the target delivery period, the electronic device can determine the delivery time window of the target residence point in the target delivery period by means of a scanning line. Specifically, when a scan line intersects with the probability distribution of the number of times of casting, projection of two consecutive intersection points on the horizontal axis (time dimension) can form a candidate distribution time window, at this time, the order casting ratio in the time window between the two intersection points is greater than or equal to the preset order casting ratio, and the duration of the time window between the two intersection points is less than or equal to the preset time window threshold.

Fig. 5 is a schematic diagram illustrating determining a delivery time window based on a probability distribution of the number of times of the delivery and a preset time window threshold in an embodiment of the present application. As shown in fig. 5, a horizontal scan line (thick solid line) is used to be placed at the top of the probability distribution of the number of times of the betting (the value with the highest probability, i.e. the value with the largest number of times of the betting after the transition between 0 and 1), then the scan line is controlled to move from top to bottom, when the scan line reaches the thick dashed line, the upper half of the scan line includes a time window [ a, B ], and the amount of orders to be betted in the time window [ a, B ] is just greater than or equal to P% of the total amount of orders, i.e. the amount of the orders to be betted in the time window [ a, B ] is greater than or equal to the preset amount of the orders to be betted, and then it is determined whether the length of the time window [ a, B ] is smaller than the preset time window threshold (K minutes).

If the above conditions are satisfied, the time window [ a, B ] satisfies that the order quantity contained in the time window [ a, B ] is just greater than or equal to P% of the total order quantity, and the time span of the time window is not greater than the set time window threshold K, so that the time window [ a, B ] is the delivery time window of the target residence point to be determined in the target delivery period.

Alternatively, in practice, p=60, k=120. It can be understood that the specific values of P and K may also be adjusted according to actual situations, which will not be described herein.

It should be noted that, in another possible design of the present application, after obtaining the probability distribution of the number of times of the betting of the target delivery period, the electronic device may further use a horizontal scan line (thick solid line) to be placed at the lowest end of the probability distribution of the number of times of the betting (the value with the lowest probability, that is, the value with the smallest number of times of the betting after changing to between 0 and 1), then control the scan line to move from bottom to top, when the scan line reaches the thick dashed line, the upper half of the scan line includes a time window [ a, B ], and if the length of the time window [ a, B ] is less than or equal to the preset time window threshold, then determine if the number of orders to be betted in the time window [ a, B ] is greater than or equal to P% of the total number of orders.

The embodiment of the application is not limited to the implementation scheme of determining the delivery time window of the target residence point in the target delivery period, and the determination can be performed according to the actual requirement, and the description is omitted here.

According to the logistics distribution information processing method provided by the embodiment of the application, at least one target resident point is determined according to the receiving address information of each order in the target order set, then at least one target distribution time period of the target resident point is determined according to the preset time granularity and the preset distribution time for each target resident point, the time of the target in each time period included in each target distribution time period is determined according to the preset time granularity, the time of the target in each time period included in the target distribution time period is subjected to normalization processing, the time probability distribution of the target distribution time period is obtained, and finally the distribution time window of the target resident point in the target distribution time period is determined according to the time probability distribution of the target distribution time period, the preset order time distribution value and the preset time window threshold. According to the technical scheme, the delivery time window of the target residence point in the target delivery time period can be mined based on the order with accurate delivery time, and implementation conditions are provided for subsequently improving the delivery efficiency of the order.

On the basis of the above embodiment, fig. 6 is a schematic flow chart of a third embodiment of the method for processing logistics distribution information provided by the present application. In the embodiment of the present application, the step S202 may be implemented as follows:

S601, determining all residence points in the distribution track data according to a preset track point distance threshold and a preset time interval threshold.

In the embodiment of the present application, the dwell point in the delivery trajectory data refers to a trajectory in which the moving speed of the target is small, and represents that the target stays in a small area for a certain period of time. The electronic device may use the points of residence to detect the actual consignment of the digger to deliver the goods to the user.

By way of example, embodiments of the present application may use a preset trajectory point distance threshold (e.g., D meters) and a preset time interval threshold (e.g., T seconds) to detect a dwell point.

Specifically, from the first track point in the delivery track data, the longest track with a distance not exceeding D meters from a certain track point is determined in sequence, and further, if the duration of the track exceeds T seconds, the track is considered as a residence point. Accordingly, all dwell points in the delivery trajectory data may be determined based on a similar approach.

For example, in the specific practice of the application, the preset track point distance threshold D may take a value of 20 meters, and the preset time interval threshold T may take a value of 30 seconds. The embodiment of the application is not limited to the specific values of D and T, and can be set according to actual requirements.

S602, according to order delivery information, receiving address information, receiving time and delivery time of each order are determined.

In the embodiment of the application, after the electronic device obtains the order distribution information, the distribution information and/or the sign-in information of each order, for example, the receiving address information, the receiving time, the distribution time and the like of the order can be determined by analyzing each order, and further, the candidate residence point set corresponding to each order is determined based on the distribution information and the sign-in information.

S603, determining a candidate resident point set of each order according to the receiving address information, the receiving time and the delivery time of each order, wherein the candidate resident point set comprises at least one resident point.

Optionally, in order to determine whether the time for the order is accurate, and verify the feasibility of correcting the time for the order by using the residence point, the electronic device may perform a space-time range query with the receiving address of each order as the center after acquiring the receiving address information, the receiving time and the delivery time of each order, so as to determine the residence point that may be used for the order.

For example, the electronic device may perform a spatio-temporal range query with the receiving address as a center point, the radius R m, the receiving time of the order as a start time, the time to pick up the order recorded by the dispatcher as an end time, and determine a set of all the points falling within the range as a candidate set of points for the order.

It will be appreciated that the consignment of the order by the dispatcher should occur at one of the candidate set of residents within the spatio-temporal range.

For example, in a specific application, it is found through practice that the residence point generated by actual consignment of each order is substantially within 70m of the coordinates of the receiving address, and thus, in this embodiment, the radius R may be a value of 70m. It will be appreciated that the radius R may be other values, and the application is not limited thereto.

S604, determining a target order set according to the candidate resident point set of each order and the delivery time of the order.

Wherein the target order comprises: an order with accurate actual time and an order with corrected time.

In the embodiment of the present application, after determining the candidate residence point set of each order, the electronic device may further combine the residence time of each residence point in the candidate residence point set and the delivery time of each order recorded by the delivery person, to determine an order with accurate actual delivery time from all orders corresponding to the delivery information of the order.

For the orders with inaccurate actual time, whether the orders can be corrected can be judged, if so, the orders with accurate actual time and the corrected orders with accurate time are corrected, and then the set of the orders with accurate actual time and corrected time is determined as the target order set.

The specific implementation of this step may be referred to as description of the embodiment shown in fig. 7 below, and will not be repeated here.

According to the logistics distribution information processing method provided by the embodiment of the application, all residence points in distribution track data are determined according to the preset track point distance threshold and the preset time interval threshold, then the receiving address information, the receiving time and the distribution time of each order are determined according to order distribution information, further the candidate residence point set of each order is determined, and finally the target order set with accurate time is determined according to the candidate residence point set of each order and the distribution time of the order. In the scheme, the order with accurate time is the basis for determining the accurate distribution time window later, so that the basis is laid for providing distribution efficiency.

Further, on the basis of the embodiment shown in fig. 6, fig. 7 is a schematic flow chart of a fourth embodiment of the method for processing logistics distribution information provided by the present application. In the embodiment of the present application, the step S604 may be implemented as follows:

S701, determining an intermediate time stamp of each resident point according to the start-stop time of each resident point in the candidate resident point set corresponding to each order.

In the embodiment of the application, since the resident points are a smaller area where the target stays in a certain time period, after the candidate resident point set corresponding to each order is determined, the start and stop time of each resident point can be determined by analyzing the distribution track data, and then the intermediate time between the start time and the end time of each resident point is calculated according to the start time and the end time of each resident point and is used as the intermediate timestamp of the corresponding resident point.

S702, determining an order with accurate actual time and an order with delayed actual time according to the middle time stamp of the resident point in the candidate resident point set corresponding to each order, the delivery time of the order and a preset time threshold.

In the embodiment of the present application, since the residence point in the candidate residence point set corresponding to each order is determined by centering on the receiving address, presetting the radius as the radius, taking the receiving time of the order as the starting time, and taking the time of the delivery recorded by the deliverer as the ending time, if the time generated by a certain residence point is very close to the delivery time recorded by the deliverer, the delivery time recorded by the deliverer is considered to be accurate, that is, the order is determined to be an order with accurate delivery time.

For example, the electronic device may determine whether the actual time to fill of the order is accurate according to the following manner, which is specifically implemented as follows:

If the intermediate time stamp of all the resident points in the candidate resident point set corresponding to each order and the delivery time of the order do not meet the preset time threshold, determining that the order is an order with actual time delay.

In practical applications, the preset time threshold may refer to a smaller period of time, for example, 5 minutes. Because the delivery time recorded by the dispatcher generally does not advance, but the recorded delivery time is delayed due to some limiting factors, the embodiment of the application can judge whether the actual delivery time of the order is accurate according to the time period that the middle time stamp of all the resident points in the candidate resident point set of the order is in the preset time threshold before the delivery time of the order.

For example, if an intermediate timestamp for a point in a set of candidate points for an order is generated within the first 5 minutes of the delivery time recorded by the dispatcher, the delivery time is considered to be accurate, i.e., the order is an order with accurate actual delivery time.

If no resident point with an intermediate time stamp generated within the first 5 minutes of the delivery time recorded by the delivery person exists in the candidate resident point set corresponding to a certain order, the delivery time delay is considered, namely the order is an order with an actual time delay.

S703, processing the order with the actual time delay according to the number of the resident points in the candidate resident point set and/or the middle time stamp of the resident points corresponding to the order with the actual time delay, and obtaining the order with the corrected time delay.

In the embodiment of the application, for the determined order with the actual time delay, the electronic device can determine whether the time delay correction can be performed on the order with the actual time delay based on the number of the resident points in the candidate resident point set corresponding to the order. And executing the process of correcting the time of the throwing for the order which can be corrected, and eliminating the related data of the order which cannot be corrected.

The electronic device processes the order with the actual time delay of the toll, for example, as follows:

If the resident point set corresponding to the order only comprises 1 resident point, correcting the delivery time of the order to be the middle time stamp of the resident point, and obtaining the order with corrected time.

Specifically, for the screened order with actual time delay, if the resident point set obtained by the space-time range query only contains 1 resident point, the order can be corrected. For example, the intermediate timestamp of the resident point may be used as the time to fill the order, resulting in a fill-time corrected order.

For the screened order with actual time delay, if the resident point set obtained by the time-space range query contains a plurality of resident points (at least two resident points), in order to avoid ambiguity of time correction, discarding the part of order data.

After the processing, the electronic equipment can take the order with accurate actual time and the order with corrected time as the basis for the statistics of the follow-up distribution time window.

According to the logistics distribution information processing method provided by the embodiment of the application, the middle time stamp of each resident point is determined according to the start-stop time of each resident point in the candidate resident point set corresponding to each order, the order with accurate actual time and the order with actual time delay are determined according to the middle time stamp of the resident point in the candidate resident point set corresponding to each order, the distribution time of the order and the preset time threshold, and the order with actual time delay is processed according to the number of resident points and/or the middle time stamp of the resident points in the candidate resident point set corresponding to the order with actual time delay, so that the order with corrected time delay is obtained. In the scheme, a target order set with accurate time for throwing can be determined according to the specific value of the residence point corresponding to each order, and a foundation is laid for the follow-up determination of an accurate delivery time window.

Further, in the above embodiments of the present application, in order to obtain the accuracy of the subsequent data processing, before the step S202, the method may further include the following steps:

In the embodiment of the application, the distribution track data is track data generated by PDA equipment carried by a logistics distributor, and a small number of serious noise points exist in the obtained distribution track data due to the influence of the PDA equipment on the external environment, namely, the recorded values of some track points possibly deviate by more than hundreds of meters from the true values in one continuous track. Thus, the delivery trajectory data may first be de-noised prior to determining the target order set for accurate time to fill using the order delivery information and delivery trajectory data.

Specifically, according to the distribution track data, the distance between two continuous track points and the time stamp difference value (i.e. instant time) between the two continuous track points are determined first, and then the ratio of the distance between every two continuous track points to the time stamp difference value between the two continuous track points is calculated. And finally, comparing the difference value with a preset speed threshold value in the electronic equipment, if the difference value is larger than the preset speed threshold value, considering that two continuous track points are unreasonable, removing the two continuous track points, and if the difference value is larger than or equal to the preset speed threshold value, reserving the two continuous track points.

In practical application, the preset speed threshold value can be 54 km/h, and the speed threshold value cannot be exceeded by a dispatcher walking or driving a dispatching vehicle in an actual scene, so that the track points with larger influence can be removed through the processing, and the accuracy of a follow-up determined dispatching time window is improved.

The foregoing embodiments introduce the technical solutions of the present application, and the following description explains the complete solution of the present application with reference to a drawing.

Fig. 8 is a block diagram of a fifth embodiment of a method for processing logistics distribution information according to the present application. As shown in fig. 8, the technical scheme of the present application mainly includes three steps: data preprocessing, time correction and time window mining.

In a first step, the delivery trajectory data and the order delivery data are preprocessed. Specifically, track denoising processing is performed on the distribution track data, then dwell point detection and the like are performed based on the denoised distribution track processing, and finally space-time range query is performed based on the processed order distribution data and dwell points obtained through detection, so that candidate dwell point sets corresponding to each order are obtained.

In the second step, based on the time generated by each resident point in the candidate resident point set corresponding to each order, determining whether the time of the order is accurate, and obtaining the order with accurate time of the order. The order with accurate time of putting includes: an order with accurate actual time and an order with corrected time, wherein the order is delayed in actual time but corrected in time.

And thirdly, determining a delivery time window of the target residence point in the target delivery period by utilizing a scanning line algorithm based on the obtained order with accurate delivery time. The distribution time window can be used for planning logistics distribution paths, and lays a foundation for subsequently improving distribution efficiency.

As can be seen from the above, in the embodiment of the present application, by using track data mining, stay point detection, and space-time range query, accurate time of the closing action in logistics distribution is obtained based on distribution track data, so that an accurate time window is mined, and the problem of poor distribution path optimization results caused by inaccurate closing time recording by a distributor in a logistics system is effectively solved.

The following are examples of the apparatus of the present application that may be used to perform the method embodiments of the present application. For details not disclosed in the embodiments of the apparatus of the present application, please refer to the embodiments of the method of the present application.

Fig. 9 is a schematic structural diagram of an embodiment of a processing device for logistics distribution information provided by the present application. As described with reference to fig. 9, the apparatus may include: an acquisition module 901, a first processing module 902 and a second processing module 903.

The acquiring module 901 is configured to acquire order distribution information and distribution track data;

A first processing module 902, configured to determine a target order set with accurate time for putting in according to the order distribution information and the distribution track data;

A second processing module 903, configured to determine a delivery time window of the target residence point in the target delivery period according to the target order set and a preset constraint condition.

In one possible design of the present application, the second processing module 903 is specifically configured to:

In another possible design of the present application, the first processing module 902 is specifically configured to:

In this possible design of the present application, the first processing module 902 is configured to determine, according to the candidate residence point set of each order and the delivery time of the order, the target order set, specifically:

the first processing module 902 is specifically configured to:

Optionally, the first processing module 902 is configured to determine, according to the intermediate timestamp of the resident point in the candidate resident point set corresponding to each order, the delivery time of the order, and a preset time threshold, an order with accurate actual time and an order with delayed actual time, where the steps are specifically:

The first processing module 902 is specifically configured to determine that the order is an order with accurate actual time when an intermediate timestamp of at least one resident point exists in each candidate resident point set corresponding to the order and the delivery time of the order meet a preset time threshold, and determine that the order is an order with delayed actual time when the intermediate timestamps of all resident points in each candidate resident point set corresponding to the order and the delivery time of the order do not meet the preset time threshold.

In this possible design of the present application, the first processing module 902 is configured to process the actual delayed order according to the number of residence points and/or the intermediate time stamps of the residence points in the candidate residence point set corresponding to the actual delayed order, so as to obtain a corrected order with the corrected time, which is specifically:

The first processing module 902 is specifically configured to, for an order with a delayed actual time, reject the order if the set of residence points corresponding to the order includes at least two residence points, and correct the delivery time of the order to be an intermediate timestamp of the residence points when the set of residence points corresponding to the order includes only 1 residence point, so as to obtain the order with corrected time.

In yet another possible design of the present application, the first processing module 902 is further configured to, before determining, according to the order delivery information and the delivery track data, a target order set with accurate delivery time, remove noise points in the delivery track data according to a preset speed threshold and a distance and time between two consecutive track points in the delivery track data, and obtain updated delivery track data.

The device provided in the embodiment of the present application may be used to perform the method in the embodiments shown in fig. 2 to 8, and its implementation principle and technical effects are similar, and are not described herein again.

It should be noted that, it should be understood that the division of the modules of the above apparatus is merely a division of a logic function, and may be fully or partially integrated into a physical entity or may be physically separated. And these modules may all be implemented in software in the form of calls by the processing element; or can be realized in hardware; the method can also be realized in a form of calling software by a processing element, and the method can be realized in a form of hardware by a part of modules. For example, the acquisition module may be a processing element that is set up separately, may be implemented in a chip of the above apparatus, or may be stored in a memory of the above apparatus in the form of program code, and the functions of the above acquisition module may be called and executed by a processing element of the above apparatus. The implementation of the other modules is similar. In addition, all or part of the modules can be integrated together or can be independently implemented. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in a software form.

For example, the modules above may be one or more integrated circuits configured to implement the methods above, such as: one or more Application SPECIFIC INTEGRATED Circuits (ASIC), or one or more microprocessors (DIGITAL SIGNAL processors, DSP), or one or more field programmable gate arrays (field programmable GATE ARRAY, FPGA), etc. For another example, when a module above is implemented in the form of processing element scheduler code, the processing element may be a general purpose processor, such as a central processing unit (central processing unit, CPU) or other processor that may invoke the program code. For another example, the modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).

In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present application, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by wired (e.g., coaxial cable, optical fiber, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk Solid STATE DISK (SSD)), etc.

Fig. 10 is a schematic structural diagram of an electronic device for executing the processing method of logistics distribution information. As shown in fig. 10, the electronic device may include: a processor 1001, a memory 1002, a communication interface 1003 and a system bus 1004, the memory 1002 and the communication interface 1003 being connected to the processor 1001 via the system bus 1004 and performing communication with each other, the memory 1002 being adapted to store a computer program executable on the processor, the communication interface 1003 being adapted to communicate with other devices, the processor 1001 implementing the solutions of the embodiments described in fig. 2 to 8 above when said computer program is executed.

In fig. 10, the processor 1001 may be a general-purpose processor including a central processing unit CPU, a network processor (network processor, NP), and the like; but may also be a digital signal processor DSP, an application specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

The memory 1002 may include random access memory (random access memory, RAM), read-only memory (RAM), and non-volatile memory (non-volatile memory), such as at least one disk memory.

The communication interface 1003 is used to enable communication between the database access apparatus and other devices (e.g., a client, a read-write library, and a read-only library).

The system bus 1004 may be a peripheral component interconnect (PERIPHERAL COMPONENT INTERCONNECT, PCI) bus, or an extended industry standard architecture (extended industry standard architecture, EISA) bus, or the like. The system bus may be classified into an address bus, a data bus, a control bus, and the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus.

Optionally, an embodiment of the present application further provides a computer readable storage medium, where computer instructions are stored, which when run on a computer, cause the computer to perform the method of the embodiment shown in fig. 2 to 8 above.

Optionally, an embodiment of the present application further provides a chip for executing instructions, where the chip is configured to perform the method of the embodiments shown in fig. 2 to fig. 8.

Embodiments of the present application also provide a program product comprising a computer program stored in a computer readable storage medium, from which at least one processor can read the computer program, the at least one processor executing the computer program implementing the method of the embodiments shown in fig. 2 to 8.

In the present application, "at least one" means one or more, and "a plurality" means two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a alone, a and B together, and B alone, wherein a, B may be singular or plural. The character "/" generally indicates that the front and rear associated objects are an "or" relationship; in the formula, the character "/" indicates that the front and rear associated objects are a "division" relationship. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b, or c may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or plural.

It will be appreciated that the various numerical numbers referred to in the embodiments of the present application are merely for ease of description and are not intended to limit the scope of the embodiments of the present application. In the embodiment of the present application, the sequence number of each process does not mean the sequence of the execution sequence, and the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present application in any way.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the application.

Claims

1. The processing method of the logistics distribution information is characterized by comprising the following steps:

acquiring order distribution information and distribution track data;

determining a delivery time window of the target residence point in the target delivery period according to the target order set and a preset constraint condition;

the determining the delivery time window of the target residence point in the target delivery period according to the target order set and the preset constraint condition comprises the following steps:

2. The method of claim 1, wherein determining a target set of orders that are accurate in time to fill based on the order delivery information and the delivery trajectory data comprises:

3. The method of claim 2, wherein the determining the target set of orders based on the candidate set of points for each order and the delivery time of the order comprises:

4. The method of claim 3, wherein determining an order with accurate actual time and an order with delayed actual time based on the intermediate time stamp of the dwell point in the candidate dwell point set corresponding to each order, the delivery time of the order, and a preset time threshold, comprises:

5. A method according to claim 3, wherein said processing said actual delayed order according to said actual delayed order corresponding to the number of points and/or intermediate timestamps of points in said candidate set of points, to obtain a corrected order comprises:

6. The method of any of claims 1-5, wherein prior to said determining a target set of orders for which the time to hand is accurate based on said order delivery information and said delivery trajectory data, said method further comprises:

7. A processing apparatus for logistics distribution information, comprising: the device comprises an acquisition module, a first processing module and a second processing module;

The second processing module is used for determining a delivery time window of the target residence point in the target delivery period according to the target order set and a preset constraint condition;

The second processing module is specifically configured to:

8. The apparatus of claim 7, wherein the first processing module is specifically configured to:

9. The apparatus of claim 8, wherein the first processing module is configured to determine the target set of orders based on the candidate set of points for each order and the delivery time of the order, specifically:

The first processing module is specifically configured to:

10. The apparatus of claim 9, wherein the first processing module is configured to determine an order with accurate actual time and an order with delayed actual time according to an intermediate timestamp of a resident point in the candidate resident point set corresponding to each order, the delivery time of the order, and a preset time threshold, specifically:

11. The apparatus of claim 9, wherein the first processing module is configured to process the actual delayed order according to the number of residence points and/or intermediate timestamps of residence points in the candidate residence point set corresponding to the actual delayed order, to obtain a corrected order, specifically:

12. The apparatus of any one of claims 7-11, wherein the first processing module is further configured to, before determining the target order set with accurate time for delivery according to the order delivery information and the delivery track data, remove noise points in the delivery track data according to a preset speed threshold and a distance and a time between two consecutive track points in the delivery track data, and obtain updated delivery track data.

13. An electronic device comprising a processor, a memory and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of the preceding claims 1-6 when executing the program.

14. A computer readable storage medium having stored therein computer instructions which, when run on a computer, cause the computer to perform the method of any of claims 1-6.