CN113762815A

CN113762815A - Logistics distribution information processing method, device, equipment and storage medium

Info

Publication number: CN113762815A
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: 2021-12-07

Abstract

The embodiment of the invention provides a method, a device, equipment and a storage medium for processing logistics distribution information. According to the technical scheme, on the basis of the obtained order distribution information, the order with accurate due time is determined by combining distribution track data, and then a preset constraint condition is combined, so that a distribution time window of a certain target residence point in a target distribution time period can be accurately determined, and goods are distributed based on the accurate distribution time window, so that the distribution efficiency of 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 start to purchase online more and more. In a business scene of e-commerce logistics distribution, improving distribution efficiency is a key factor for improving shopping experience of a user and reducing logistics cost, and determining time and place where the user can receive express in order to improve distribution efficiency is key.

In the prior art, the delivery time length of goods to be delivered is determined mainly according to 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 delivery person corresponding to the goods to be delivered, namely the required time length of the goods to be delivered from the delivery station to the delivery station, and the delivery time of the goods to be delivered on the same day is determined by combining the delivery starting time point of the goods to be delivered, so that the accurate goods delivery time is determined.

However, in a logistics distribution business scenario, an actual delivery and acceptance action of each item to be distributed occurs on line, and the actual acceptance time of each item needs a distributor to click and confirm the acceptance in a system to be recorded, and the distributor sometimes delays confirming the acceptance due to a condition limitation or the like, so that the acquired second historical delivery record information is inaccurate, and thus, the problem of low accuracy of the item delivery time determined in the prior art exists.

Disclosure of Invention

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

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 to put 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 time period according to the target order set and preset constraint conditions.

In a possible design of the first aspect, the determining a delivery time window of a target residence point in a target delivery period according to the target order set and preset constraints 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 residence point, determining at least one target delivery time period of the target residence point according to a preset threshold value of the number of appropriate deliveries and preset delivery time;

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

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

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

In another possible design of the first aspect, the determining a target order set with accurate time to put according to the order delivery information and the delivery trajectory 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, determining the receiving address information, the receiving time and the distribution appropriate time of each order;

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

determining the target order set according to the candidate residence point set of each order and the delivery time to put of the order, wherein the target order comprises: the order with accurate actual time to put and the order with corrected time to put.

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

determining a middle time stamp of each residence point according to the starting and ending time of each residence point in the candidate residence point set corresponding to each order;

determining an order with accurate actual time to put and an order with delayed actual time to put according to a middle timestamp of a stay point in a candidate stay point set corresponding to each order, the delivery time to put of the order and a preset time threshold;

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

Optionally, the determining the order with accurate actual time to put and the order with delayed actual time to put according to the middle timestamp of the stay point in the candidate stay point set corresponding to each order, the delivery time to put of the order, and the preset time threshold includes:

if the intermediate timestamp of at least one residence point exists in the candidate residence point set corresponding to each order and the delivery time to the order meets a preset time threshold, determining that the order is the order with accurate actual time to the place;

and if the intermediate timestamps of all the parking points in the candidate parking 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 the order delayed by the actual time delay of the appropriate parking.

In this possible design of the first aspect, the processing the order with the actual delay in due time according to the number of residence points and/or the middle timestamp of residence points in the candidate residence point set corresponding to the order with the actual delay in due time to obtain the order with the corrected delay in due time includes:

for an order with actual delay in due time, if the resident point set corresponding to the order contains at least two resident points, rejecting the order;

and if the residence point set corresponding to the order only comprises 1 residence point, correcting the delivery appropriate time of the order to be the middle time stamp of the residence point to obtain the order with the corrected appropriate time.

In yet another possible design of the first aspect, before the determining, according to the order delivery information and the delivery trajectory data, a target order set with accurate time to commit, the method further includes:

and removing noise points in the distribution track data according to a preset speed threshold value 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 device for processing 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 to put 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 time period according to the target order set and preset constraint conditions.

In a 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 the candidate set of residence points of each order and the delivery time for the order, specifically:

the first processing module is specifically configured to:

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

the first processing module is specifically configured to determine that the order is an order with accurate actual time to put when a middle timestamp of at least one standing point in a candidate standing point set corresponding to each order and the delivery time to put of the order meet a preset time threshold, and determine that the order is an order with delayed actual time to put when the middle timestamps of all standing points in the candidate standing point set corresponding to each order and the delivery time to put 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 order with the actual delay in the due impression time according to the number of residence points and/or a middle timestamp of the residence point in the candidate residence point set corresponding to the order with the actual delay in the due impression time, to obtain the order with the corrected due impression time, and specifically includes:

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

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

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

In a third aspect, embodiments of the present application further provide an electronic device, which includes a processor, a memory, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the method according to the first aspect and possible designs.

In a fourth aspect, embodiments of the present application further provide a computer-readable storage medium, in which computer instructions are stored, and when the computer instructions are executed on a computer, the computer is caused to execute the method according to the first aspect and each possible design.

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

Drawings

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

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

fig. 3 is a schematic flowchart 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 hit times in an embodiment of the present application;

FIG. 5 is a schematic diagram illustrating an example of determining a delivery time window based on a probability distribution of the number of successful deliveries and a preset time window threshold in the present application;

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

fig. 7 is a schematic flowchart 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 device for processing logistics distribution information provided by the present application;

fig. 10 is a schematic structural diagram of an electronic device for executing a method for processing logistics distribution information according to the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, 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 some embodiments of the present application, but 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.

With the rapid growth of economy and the rapid development of the internet industry, people start to purchase online more and more, and the network technology and the electronic commerce are rapidly developed, so that the logistics distribution industry is rapidly developed. Logistics distribution is a way of goods distribution from the point of view of the way of goods distribution. The logistics distribution can provide services for customers of electronic commerce, unified information management and scheduling are carried out on the whole logistics distribution system according to the characteristics of the electronic commerce, the goods management work is carried out in a logistics base according to the ordering requirements of users, and the prepared goods are delivered to consignees in a logistics mode.

In the physical distribution industry, especially in the scene of e-commerce logistics express delivery service, distribution efficiency is a very 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 distribution efficiency, the time window of the user is mined, namely, the time and the place where the user can receive the express are determined, and the method is very important for subsequent distribution path planning.

In the existing scheme, simple statistics is mainly performed based on data (first historical distribution record information of a distribution station where goods to be distributed are located and second historical distribution record information determined by distributors corresponding to the goods to be distributed) put in storage by a logistics system, and the simple statistics has unrealistic high requirements on the quality of logistics data, for example, all the distributors are required to accurately record the distribution appropriate time of each order. However, in an actual logistics distribution business scene, when an actual distribution due delivery behavior occurs on-line, the time of the due delivery behavior cannot be directly warehoused, a distributor clicks in the system to confirm the due delivery to be recorded, and sometimes the distributor delays the confirmation of the due delivery due to condition limitations and the like, so that the warehoused data of the logistics system is not accurate enough, 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, which includes obtaining order distribution information and distribution track data, determining a target order set with accurate time to put to a destination 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 time period according to the target order set and preset constraint conditions. According to the technical scheme, on the basis of the obtained order distribution information, the order with accurate due time is determined by combining distribution track data, and then a preset constraint condition is combined, so that a distribution time window of a certain target residence point in a target distribution time period can be accurately determined, and goods are distributed based on the accurate distribution time window, so that the distribution efficiency of goods is improved.

The technical concept of the technical scheme of the application is as follows: the reason that the accuracy of the delivery time window in the logistics delivery scene is low is mainly that the delivery due time manually recorded by a delivery person in the logistics system is not accurate, and the reason that the availability of the delivery time window is low 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, technologies such as track data mining are used for an actual business scene, according to the distribution track data of an order recorded by GPS equipment carried by a distributor, and the distribution track data is combined with logistics and e-commerce order data (order information), so that accurate distribution due time can be determined, namely, a distribution time window with interpretability and usability is obtained, and data support is provided for distribution route optimization.

Before the technical solution of the present application is introduced, an application scenario of the embodiment of the present application is first introduced.

Fig. 1 is a schematic view of an application scenario of a processing method for 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. Generally, the station is a minimum distribution site of a logistics or express company, and when the goods arrive at the distribution station, the goods are distributed to the distributors in the corresponding area, and the distributors distribute the goods.

In embodiments of the present application, the residency point may be determined based on the shipping address in the order information, and the shipping addresses of multiple orders may correspond to the same residency point. The embodiment of the application does not limit the specific relationship between the residence point and the order information.

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

Furthermore, after the electronic device determines the delivery time window of the target residence point in the target delivery time period, the electronic device can push the delivery time window of the target residence point in the target delivery time period to the deliverer, so that the deliverer can know the delivery time window of the target residence point in the target delivery time period, reference is provided for the delivery time of the deliverer, the delivery time due to goods can be prolonged, and the delivery efficiency is 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 time period, the delivery time window of the target residence point in the target delivery time period may be pushed to the terminal device first, so that the terminal device presents the delivery time window to the deliverer; if the electronic device is implemented through the terminal device, after the electronic device determines the delivery time window of the target residence point in the target delivery time period, the target residence point can be directly presented to the delivery staff.

It can be understood that, in the embodiment of the present application, a specific implementation scheme for the electronic device to push the delivery time window of the target residence point in the target delivery time period to the delivery staff is not limited, and the implementation scheme may be determined according to actual requirements, and is not described herein again.

Illustratively, the application scenario shown in fig. 1 includes 1 distribution station and 6 residence points, wherein a triangular shape represents a distribution center, a round solid point represents a residence point, an abscissa is a longitude value, and an ordinate is a latitude value. The electronic device may determine, according to the technical solution of the present application, a delivery time window of each residence point in the target delivery time period, respectively.

It can be understood that the execution subject of the embodiment of the present application may be an electronic device, for example, a terminal device such as a computer and a tablet computer, or may also be a server, for example, a background processing platform, and the like. Therefore, the present embodiment is explained by referring to the terminal device and the server collectively as the electronic device, and it can be determined as the actual situation as to whether the electronic device is specifically the terminal device or the server.

The technical solution of the present application will be described in detail below with reference to specific examples. It should be noted that the following specific 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 flowchart of a first embodiment of a method for processing logistics distribution information provided by the present application. As shown in fig. 2, the method may include the steps of:

s201, obtaining order distribution information and distribution track data.

The order delivery information may include delivery information of each order, such as receiving address information of the order, receiver information, and the like. The delivery trajectory data is mainly the moving trajectory of the deliverer or the delivery equipment, which is used for representing the position information experienced by the deliverer in the delivery process. For example, the delivery trajectory data may refer to trajectory data generated by a handheld terminal (PDA) carried by the logistics delivery staff.

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

And S202, determining a target order set with accurate appropriate time according to the order distribution information and the distribution track data.

In an embodiment of the application, the electronic device may perform residence point detection based on the acquired delivery trajectory data, so as to determine a smaller area where a delivery person or a delivery device stays in a certain time period. The actual act of committing the deliverer to deliver the goods to the user can be mined by the residence point detection.

The electronic equipment can determine information such as receiving address information, receiving time, delivery due time and the like of each order according to the order delivery information, and further determines all orders with accurate due time, namely a target order set, according to 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 that are time-to-live accurate may include only orders that are time-to-live accurate, or may include both orders that are time-to-live accurate and orders that are time-delayed but corrected for actual time-to-live. The embodiment of the present application does not limit the specific composition of all orders with accurate time to put, and may be determined according to the situation.

For a specific implementation of this step, reference may be made to the following description in the embodiment shown in fig. 4, which is not described herein again.

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

For example, in the embodiment of the present application, after obtaining the order with accurate time to put, the optimal delivery time period of each residence point in each target delivery period may be counted. Illustratively, the optimal delivery time period is also referred to as a delivery time window.

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

In practical application, for the problem of the optimization of the logistics distribution path, the electronic device is pre-configured with a preset constraint condition for a distribution time window, and the preset constraint condition is established according to the actual operation of a distributor in an actual scene.

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

1. in practical applications, for a delivery address (residence point), since the deliverer will deliver once in the morning and afternoon of each day, 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 at which most recipients can sign for express delivery on weekdays (e.g., in weeks) and on holidays (e.g., on weekends such as saturdays and sundays and holidays), the delivery time windows on weekdays and holidays are calculated for each delivery address, respectively. Therefore, for each delivery address, the delivery time window refers to one of the delivery periods of the weekday in the morning, the afternoon, the morning on the holiday, the afternoon on the holiday, and the like;

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

3. for a delivery address, the determined delivery time window needs to cover most orders of the delivery wave number (morning and/or afternoon of working day and/or holiday) to which the time window belongs, namely, the ratio of the amount of orders which can be dulled in the delivery time window to the amount of all orders delivered to the delivery address needs to be more than a preset threshold value;

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 assumed that no significant time window exists in the corresponding delivery period.

Thus, in the embodiment of the present application, the electronic device may determine a 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 to put and the preset constraint condition.

For a specific implementation of this step, reference may be made to the following description in the embodiment shown in fig. 3, which is not described herein again.

According to the logistics distribution information processing method provided by the embodiment of the application, the order distribution information and the distribution track data are obtained, the target order set with accurate due 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 time period is determined according to the target order set and the preset constraint condition. According to the technical scheme, the order with accurate due time is determined by the obtained order distribution information and distribution track data together, the preset constraint condition is combined, the distribution time window of a certain target residence point in the target distribution time period can be accurately determined, the goods are distributed based on the accurate distribution time window, and the distribution efficiency of the goods is improved.

On the basis of the foregoing embodiments, fig. 3 is a schematic flow chart of a second embodiment of the method for processing logistics distribution information provided by the present application. In an embodiment of the present application, the step S203 may be implemented by:

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

In an embodiment of the application, the electronic device determines the shipping 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 quarter, the same office, etc. Thus, a substantially identical shipping address for multiple orders may be referred to as a target 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 the residence points based on the receiving addresses.

S302, for each target residence point, determining at least one target delivery time period of the target residence point according to a preset threshold of the number of appropriate deliveries and preset delivery time.

In an embodiment of the application, the electronic device may determine that each target residence point may include four different delivery time periods, which are morning on a weekday, afternoon on a weekday, morning on a holiday, and afternoon on a holiday, according to a preset constraint condition of the delivery time window.

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

In practical applications, the daily distribution period may be divided based on a preset division time point, for example, 15:30 of each day as the division time point in the morning and afternoon of the day, etc. It is understood 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 successful deliveries is set to distinguish whether the delivery time interval is a target delivery time interval for which the delivery time window needs to be determined. If the number of the successful delivery times in a certain delivery time period is smaller than a preset threshold value of the successful delivery times, the delivery time window obtained by mining is considered to have no statistical significance, and therefore the delivery time period does not belong to the target delivery time period.

Alternatively, in practical applications, the preset threshold of the number of successful throws may be 20. It is understood that the preset threshold of the number of times of the successful delivery may be other values, and is not limited herein.

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

In the embodiment of the application, for each target delivery time interval of each determined target residence point, in order to accurately determine the number of times of the commits in each time interval, a preset time granularity is set, so that the electronic device can perform the statistics of the number of times of the commits in all the time intervals included in the target delivery time interval by taking the preset time granularity as a unit in the calculation process.

For example, in practical applications, the preset time granularity may be minutes, that is, for the target residence point, the electronic device may count the number of tolls occurring per minute for each target delivery period.

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

In the embodiment of the application, after counting the number of times of the tolls in each time period included in each target distribution period of each target residence point, the electronic device may transform the number of times of the tolls in each time period included in each target distribution period to 0 to 1 through normalization processing, and continuously process the transformed number of times of the tolls corresponding to all the time periods in the target distribution period, so as to obtain the probability distribution of the number of times of the tolls in the target distribution period.

Illustratively, when the electronic device counts the number of times of the tolls occurring in each minute in each target distribution period, the number of times of the tolls in each minute may be unified to be between 0 and 1 through the normalization process, so as to obtain the probability distribution of the number of times of the tolls in the target distribution period.

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

Illustratively, W may be 10. It can be understood that the embodiment of the present application does not limit the specific value of W, and it can be set according to actual requirements.

Exemplarily, fig. 4 is a schematic diagram of probability distribution of the number of successful commits in the embodiment of the present application. Referring to fig. 4, a thin solid line is a probability distribution curve of the number of times of justice of a certain target residence point in a certain target distribution period, the horizontal axis represents time in minutes, the starting point represents the starting time of the target distribution period in 0 minutes, the ending time represents 1400 minutes, and the vertical axis represents the number of times of justice after the normalization process, and the value is between 0 and 1, for example, between 0 and 0.8.

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

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

For example, fig. 5 is a schematic diagram illustrating a distribution time window determined based on the probability distribution of the number of successful deliveries and a preset time window threshold in the embodiment of the present application. As shown in fig. 5, a horizontal scanning line (thick solid line) is used to be placed at the top of the probability distribution of the number of times of punts (the value with the highest probability, that is, the value with the highest number of times of punts after the conversion to 0-1), and then the scanning line is controlled to move from top to bottom, when the scanning line reaches the thick dotted line, the upper half of the scanning line includes a time window [ a, B ], and the amount of orders punted in the time window [ a, B ] is just greater than or equal to P% of the total amount of orders, that is, the order punt ratio in the time window [ a, B ] is greater than or equal to the preset order punt ratio, and then whether the length of the time window [ a, B ] is less than the preset time window threshold (K minutes) is determined.

If the above conditions are met, the time window [ A, B ] meets the condition that the contained order amount is just greater than or equal to P% of the total order amount, and the time span thereof does not exceed the set time window threshold value 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 is 60 and K is 120. It can be understood that the specific values of P and K may also be adjusted according to actual situations, and are not described herein again.

It should be noted that, in another possible design of the present application, after obtaining the probability distribution of the numbers of commits in the target distribution time period, the electronic device may further use a horizontal scanning line (thick solid line) to be placed at the lowest end of the probability distribution of the numbers of commits (the value with the lowest probability, that is, at the value with the lowest number of commits after being converted to 0-1), then control the scanning line to move from bottom to top, when the scanning line reaches the thick dotted line, the upper half of the scanning line includes a time window [ a, B ], and whether the length of the time window [ a, B ] is less than or equal to a preset time window threshold, and when the length of the time window [ a, B ] is less than or equal to the preset time window threshold, determine whether the number of commits in the time window [ a, B ] is greater than or equal to P% of the total order number.

The embodiment of the present application does not limit an implementation scheme for determining a delivery time window of a target residence point in a target delivery time period, and may determine the target residence point according to actual requirements and is not described herein again.

The logistics distribution information processing method provided by the embodiment of the application determines at least one target residence point according to the receiving address information of each order in the target order set, then determines at least one target distribution time period of the target residence point according to a preset threshold value of the number of times of justice and preset distribution time for each target residence point, determines the number of times of justice in each time period included in each target distribution time period according to a preset time granularity, performs normalization processing on the number of times of justice in each time period included in the target distribution time period to obtain the probability distribution of the number of times of justice in the target distribution time period, and finally determines the distribution time window of the target residence point in the target distribution time period according to the probability distribution of the number of times of justice in the target distribution time period, a preset ratio of the number of justice and a preset time window threshold value. In the technical scheme, the delivery time window of the target residence point in the target delivery time period can be excavated based on the order with accurate appropriate delivery time, and realization conditions are provided for subsequently improving the delivery efficiency of the order.

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

s601, determining all the 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 section of 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 residence point to detect actual commit behavior of the excavation deliverer to deliver the cargo to the user.

For example, the embodiment of the present application may use a preset track point distance threshold (e.g., D meters) and a preset time interval threshold (e.g., T seconds) to detect the stay point.

Specifically, the longest track with the distance not exceeding D meters from a certain track point is sequentially determined from the first track point in the distribution track data, and further, if the duration of the track exceeds T seconds, the track is considered as a staying point. Accordingly, all the stagnation points in the delivery trajectory data can be determined based on a similar method.

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

S602, according to the order distribution information, determining the receiving address information, the receiving time and the distribution due time of each order.

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

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

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

For example, the electronic device may perform a spatiotemporal range query with the shipping address as a center point, the radius as R meters, the receiving time of the order as a starting time, and the due time recorded by the deliverer as an ending time, and determine a set of all residence points falling within the range as a candidate set of residence points for the order.

It is to be appreciated that the delivery of the order by the dispenser should occur at one of the set of candidate residence points within the spatio-temporal range.

Illustratively, in a specific application, it is found by practice that the residence point generated by actual due delivery of each order is substantially within 70m of the coordinates of the shipping address, and therefore, in this embodiment, the value of the radius R may be 70 m. It is understood that the value of the radius R may be other values, and the present application does not limit the value.

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

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

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

For an order with inaccurate actual time to put in, whether correction is possible or not can be judged, if so, the order can be corrected, and further, the order with accurate actual time to put in and the order set with corrected time to put in are determined as the target order set.

For specific implementation of this step, reference may be made to the following description of the embodiment shown in fig. 7, which is not described herein again.

According to the logistics distribution information processing method provided by the embodiment of the application, all the stay points in distribution track data are determined according to the preset track point distance threshold and the preset time interval threshold, the receiving address information, the receiving time and the distribution time of each order are determined according to the order distribution information, the candidate stay point set of each order is determined, and finally the target order set with accurate time to be paid is determined according to the candidate stay point set of each order and the distribution time of the order. In the scheme, the order with accurate proper time is the basis for subsequently determining the accurate delivery time window, so that the basis is laid for providing the delivery 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 an embodiment of the present application, the step S604 may be implemented by:

s701, determining a middle time stamp of each residence point according to the starting and ending time of each residence point in the candidate residence point set corresponding to each order.

In the embodiment of the application, since the residence point is a certain small area where the target stays in a certain time period, after the candidate residence point set corresponding to each order is determined, the delivery trajectory data is analyzed, so that the start-stop time of each residence point can be determined, and further, according to the start time and the end time of each residence point, the middle time between the start time and the end time of each residence point is calculated and used as the middle timestamp of the corresponding residence point.

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

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

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

if the intermediate timestamp of at least one residence point exists in the candidate residence point set corresponding to each order and the delivery time to the order meets the preset time threshold, determining that the order is the order with accurate actual time to the place;

and if the intermediate time stamps of all the parking points in the candidate parking 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 the order delayed by the actual time delay of the appropriate parking.

In practical applications, the preset time threshold may refer to a small time period, for example, 5 minutes. Since the delivery time to put recorded by the delivery person is generally not advanced in a normal situation, but the recorded delivery time to put is delayed due to some limiting factors, the embodiment of the present application may determine whether the actual time to put of the order is accurate according to a time period in which the intermediate timestamps of all the residence points in the candidate residence point set of the order are located before the delivery time to put of the order by a preset time threshold.

Illustratively, if the intermediate timestamp of an order corresponding to one of the set of candidate waypoints for which there is a waypoint is generated within the first 5 minutes of the delivery time-to-live recorded by the delivery operator, the delivery time-to-live is considered accurate, i.e., the order is an order for which the actual time-to-live is accurate.

And if the residence point with the intermediate timestamp generated in the first 5 minutes of the delivery due time recorded by the delivery personnel does not exist in the candidate residence point set corresponding to a certain order, considering that the delivery due time is delayed, namely the order is the order with the actual due time delayed.

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

In an embodiment of the application, for an order with a determined actual delay in time to put in place, the electronic device may determine whether to perform correction of the actual delay in time to put in place on the order with the determined actual delay in time to put in place based on the number of residence points in the candidate set of residence points corresponding to the order. For orders that can be corrected, the processing of correcting the appropriate time is executed, and for orders that cannot be corrected, the relevant data is removed.

For example, the electronic device processes the order delayed by the actual time to put it properly as follows:

for an order with actual delay of due time, if the resident point set corresponding to the order contains at least two resident points, the order is rejected;

Specifically, for the screened order with delayed actual due posting time, if the dwelling point set obtained by the space-time range query only contains 1 dwelling point, it indicates that the order can be corrected. For example, the intermediate timestamp of the residence point may be used as the time to commit for the order, thereby obtaining a time to commit corrected order.

For the screened orders with delayed actual due time, if the resident point set obtained by the space-time range query comprises a plurality of resident points (at least two resident points), in order to avoid ambiguity of correction of the due time, the part of order data is discarded.

After the processing, the electronic device can use the order with accurate actual time to put and the order with corrected time to put as the basis for the statistics of the subsequent distribution time window.

According to the method for processing the logistics distribution information, the middle timestamp of each standing point is determined according to the starting and ending time of each standing point in the candidate standing point set corresponding to each order, the order with accurate actual time to put and the order with delayed actual time to put are determined according to the middle timestamp of each standing point in the candidate standing point set corresponding to each order, the distribution time to put of the order and the preset time threshold, and the order with delayed actual time to put is processed according to the number of the standing points and/or the middle timestamp of the standing points in the candidate standing point set corresponding to the order with delayed actual time to put, so that the order with the corrected time to put is obtained. According to the scheme, the target order set with accurate due time can be determined according to the specific value of the residence point corresponding to each order, and a foundation is laid for determining the accurate distribution time window subsequently.

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

In the embodiment of the present application, the distribution track data is based on track data generated by a PDA device carried by a logistics distributor, and due to the influence of the PDA device in the external environment, a small number of serious noise points may exist in the obtained distribution track data, that is, recorded values of some track points may deviate from real values by more than hundreds of meters in a continuous track. Therefore, before determining a target order set with accurate due time by using order distribution information and distribution track data, the distribution track data may be denoised first.

Specifically, according to the distribution track data, the distance between two continuous track points and the timestamp difference (i.e., time) between the two continuous track points are determined, and then the ratio of the distance between every two continuous track points and the timestamp difference 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 greater than the preset speed threshold value, considering that two continuous track points are unreasonable, and removing the two continuous track points, and if the difference value is greater than or equal to the preset speed threshold value, keeping the two continuous track points.

In practical application, the preset speed threshold value can be 54 kilometers per hour, and since the speed threshold value cannot be exceeded by a distributor when the distributor walks and drives a distribution vehicle in a practical scene, track points with large influence can be removed through the processing, and the precision of a subsequent determined distribution time window is improved.

The above embodiments describe the technical solutions of the present application, and the following is a complete solution of the present application through a drawing.

Fig. 8 is a block diagram of a fifth exemplary embodiment of the logistics distribution information processing method provided by the present application. As shown in fig. 8, the technical solution of the present application is mainly divided into three steps: data preprocessing, appropriate time correction and time window mining.

In the first step, delivery trajectory data and order delivery data are preprocessed. Specifically, track denoising processing is performed on the delivery track data, then residence point detection is performed on the basis of the delivery track processing after denoising, and finally space-time range query is performed on the basis of the processed order delivery data and the residence points obtained through detection, so that a candidate residence point set corresponding to each order is obtained.

And in the second step, determining whether the time for putting the order is accurate or not based on the time generated by each residence point in the candidate residence point set corresponding to each order, and obtaining the order with accurate time for putting the order. The order with accurate time to put includes: the order with accurate actual time to put and the order with corrected time to put which is obtained by delaying the actual time to put but correcting the actual time to put.

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

In summary, the embodiment of the application utilizes track data mining, residence point detection and time-space range query, and obtains accurate time of the due delivery behavior in logistics distribution based on distribution track data, so that an accurate time window is mined, and the problem of poor distribution path optimization result caused by inaccurate recording of the due delivery time by a distributor in a logistics system is effectively solved.

The following are embodiments of the apparatus of the present application that may be used to perform embodiments of the method of the present application. For details which are not disclosed in the embodiments of the apparatus of the present application, reference is made to the embodiments of the method of the present application.

Fig. 9 is a schematic structural diagram of an embodiment of a processing apparatus for logistics distribution information provided in 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 obtaining module 901 is configured to obtain order distribution information and distribution track data;

a first processing module 902, configured to determine, according to the order distribution information and the distribution trajectory data, a target order set with accurate time to put the order;

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

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 the target order set according to the candidate residence point set of each order and the delivery time for the order, specifically:

the first processing module 902 is specifically configured to:

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

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

In this possible design of the application, the first processing module 902 is configured to process the order with the actual delay in the due impression time according to the number of residence points and/or a middle timestamp of the residence point in the candidate residence point set corresponding to the order with the actual delay in the due impression time, to obtain the order with the corrected due impression time, and specifically includes:

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

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

The apparatus provided in the embodiment of the present application may be used to execute the method in the embodiments shown in fig. 2 to fig. 8, and the implementation principle and the technical effect are similar, which are not described herein again.

It should be noted that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity, or may be physically separated. And these modules can be realized in the form of software called by processing element; or may be implemented entirely in hardware; and part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. For example, the obtaining module may be a processing element separately set up, or may be implemented by being integrated in a chip of the apparatus, or may be stored in a memory of the apparatus in the form of program code, and a processing element of the apparatus calls and executes the functions of the obtaining module. Other modules are implemented similarly. In addition, all or part of the modules can be integrated together or can be independently realized. 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 the form of software.

For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when some of the above modules are implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor that can call program code. As another example, these modules may be integrated together, implemented in the form of a system-on-a-chip (SOC).

In the above embodiments, the implementation may be wholly or partially realized 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, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.

Fig. 10 is a schematic structural diagram of an electronic device for executing a method for processing logistics distribution information according to the present application. 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, wherein the memory 1002 and the communication interface 1003 are connected with the processor 1001 through the system bus 1004 and are used for mutual communication, the memory 1002 is used for storing computer programs capable of running on the processor, the communication interface 1003 is used for communicating with other devices, and the processor 1001 executes the computer programs to realize the scheme of the embodiment shown in the above fig. 2 to 8.

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

The memory 1002 may include a Random Access Memory (RAM), a read-only memory (RAM), and a non-volatile memory (non-volatile memory), such as at least one disk memory.

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

The system bus 1004 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The system bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown, but this does not mean that there is 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, and when the computer instructions are executed on a computer, the computer is caused to execute the method according to the embodiment shown in fig. 2 to 8.

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

Embodiments of the present application further provide a program product, where the program product includes a computer program, where the computer program is stored in a computer-readable storage medium, and the computer program can be read by at least one processor from the computer-readable storage medium, and the at least one processor can implement the method in the embodiments shown in fig. 2 to 8 when executing the computer program.

In the present application, "at least one" means one or more, "a plurality" means two or more. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone, wherein A and B can be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship; in the formula, the character "/" indicates that the preceding and following related objects are in a relationship of "division". "at least one of the following" or similar expressions refer to any combination of these items, including any combination of the singular or plural items. 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 multiple.

It is to be understood that the various numerical references referred to in the embodiments of the present application are merely for descriptive convenience and are not intended to limit the scope of the embodiments of the present application. In the embodiment of the present application, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiment of the present application.

Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for processing logistics distribution information is characterized by comprising the following steps:

acquiring order distribution information and distribution track data;

2. The method of claim 1, wherein determining a delivery time window for a target stop in a target delivery period based on the target order set and preset constraints comprises:

3. The method of claim 1, wherein said determining a target order set with accurate time to commit based on said order delivery information and said delivery trajectory data comprises:

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

5. The method of claim 4, wherein determining the order with accurate actual time to put and the order with delayed actual time to put according to the intermediate timestamp of the residence point in the candidate residence point set corresponding to each order, the delivery time to put of the order, and the preset time threshold comprises:

6. The method of claim 4, wherein processing the order with the actual delay in time to arrive at the corrected order for delay in time to put according to the number of points to put in the candidate set of points to put in place and/or the timestamp of the points to put in place in the set of points to put in place comprises:

7. The method of any of claims 1-6, wherein prior to said determining a target order set with accurate time to commit from said order delivery information and said delivery trajectory data, said method further comprises:

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

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

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

11. The apparatus of claim 10, wherein the first processing module is configured to determine the target order set according to the candidate set of residence points for each order and the delivery time for the order, and specifically:

the first processing module is specifically configured to:

12. The apparatus of claim 11, wherein the first processing module is configured to determine, according to a middle timestamp of a residence point in the candidate residence point set corresponding to each order, a delivery time to the order, and a preset time threshold, an order with an accurate actual time to put and an order with a delayed actual time to put that are specifically:

13. The apparatus according to claim 11, wherein the first processing module is configured to process the order with the actual delay in the due time according to the number of residence points and/or the middle timestamp of the residence point in the candidate residence point set corresponding to the order with the actual delay in the due time, so as to obtain the order with the corrected due time, and specifically:

14. The apparatus according to any one of claims 8 to 13, wherein the first processing module is further configured to, before determining a target order set with an accurate time to commit according to the order distribution information and the distribution track data, remove noise points in the distribution track data according to a preset speed threshold and a distance and a time between two consecutive track points in the distribution track data to obtain updated distribution track data.

15. 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 claims 1-7 when executing the program.

16. A computer-readable storage medium having stored thereon computer instructions which, when executed on a computer, cause the computer to perform the method of any one of claims 1-7.