CN113935561A

CN113935561A - Method, device and system for distributing and dispatching tasks and computer readable storage medium

Info

Publication number: CN113935561A
Application number: CN202010667547.2A
Authority: CN
Inventors: 张培行; 李磊; 刘琼; 路高飞; 张素墁; 叶嘉韬; 林宁杰; 黄琦
Original assignee: SF Technology Co Ltd
Current assignee: SF Technology Co Ltd
Priority date: 2020-07-13
Filing date: 2020-07-13
Publication date: 2022-01-14

Abstract

The application provides a method for distributing delivery tasks, which comprises the steps of obtaining logistics data associated with a transportation object, wherein the logistics data comprise position information of the transportation object and delivery task data associated with a logistics node; predicting the time when the transportation object reaches the logistics node based on the position information of the transportation object; obtaining dispatching data historically distributed by the logistics nodes; determining distribution proportion of dispatching objects based on dispatching data of the historical distribution; and determining dispatching task distribution time and dispatching task distribution quantity of the dispatching object based on the time of the transportation object reaching the logistics node, the dispatching task data and the distribution proportion. The dispatching task distribution quantity and the dispatching task distribution time of the dispatching object are predicted through the logistics information and the logistics node data, the dispatching object can reasonably arrange the dispatching path and the dispatching tool conveniently, the working efficiency is improved, and the dispatching cost of the dispatching tool is reduced.

Description

Method, device and system for distributing and dispatching tasks and computer readable storage medium

Technical Field

The application relates to the technical field of logistics, in particular to a method, a device and a system for distributing and dispatching tasks and a computer readable storage medium.

Background

In recent years, the logistics industry has been intelligentized and has been rapidly developing, and the popularity has been gradually shifted from the labor intensive type in the past to the intelligent labor type. Taking express delivery as an example, the express delivery mainly comprises logistics transportation and a delivery link, the delivery link is an important link for a waybill to reach a client from a business network, however, the delivery link has the characteristic of multiple and dispersed distribution places, so that the working efficiency of the delivery link is low, and therefore, how to improve and optimize the quality and efficiency of the delivery link at the end of logistics is of great significance to the intelligent development of the logistics industry.

Disclosure of Invention

The application provides a method, a device, a system and a computer readable storage medium for distributing and dispatching tasks, which aim to solve the problem that the work efficiency of the current dispatching link in the logistics industry is low.

In one aspect, the present application provides a method for distributing dispatch tasks, the method comprising: acquiring logistics data associated with a transportation object, wherein the logistics data comprises position information of the transportation object and dispatching task data associated with logistics nodes; predicting the time when the transportation object reaches the logistics node based on the position information of the transportation object; obtaining dispatching data historically distributed by the logistics nodes; determining distribution proportion of dispatching objects based on dispatching data of the historical distribution; and determining dispatching task distribution time and dispatching task distribution quantity of the dispatching object based on the time of the transportation object reaching the logistics node, the dispatching task data and the distribution proportion.

In some embodiments, the predicting the time at which the transportation object arrives at the logistics node based on the location information of the transportation object comprises: acquiring historical average arrival time of the transportation object reaching the logistics node; and predicting the time of the transportation object reaching the logistics node based on the historical average arrival time.

In some embodiments, the obtaining the historical average arrival time of the transportation object at the logistics node comprises: acquiring historical logistics data associated with the position information of the transport object; and determining the historical average arrival time of the transportation object to the logistics node based on the historical logistics data.

In some embodiments, the historical logistics data comprises historical departure times, historical departure locations, historical arrival times, and historical arrival locations, and the determining the historical average arrival time of the transportation object at the logistics node based on the historical logistics data comprises: determining correlated historical logistics data based on the historical logistics data, wherein a historical departure place of the correlated historical logistics data is correlated with the position information of the transportation object, and a historical arrival place of the correlated historical logistics data is correlated with the logistics node; determining a historical average arrival time based on the correlated historical logistics data.

In some embodiments, the historically assigned dispatch data includes shift information, and determining an allocation proportion of dispatch objects based on the historically assigned dispatch data includes: determining the historical dispatch data of the shift related to the arrival time of the transportation object at the logistics node based on the shift information; determining a shift allocation proportion of the dispatch object based on the shift history dispatch data.

In some embodiments, the determining the dispatch task allocation time and the dispatch task allocation quantity of the dispatch object based on the time of arrival of the transport object at the logistics node, the dispatch task data, and the allocation proportion comprises: acquiring shift data of the logistics nodes; determining the shift of the transportation object to the logistics node based on the shift data of the logistics node and the time of the transportation object to the logistics node; and determining the dispatching task distribution quantity of the dispatching object based on the shift of the transportation object reaching the logistics node and the shift distribution proportion.

In some embodiments, the historically assigned dispatch data includes unit area information, and the determining an allocation proportion of dispatch objects based on the historically assigned dispatch data includes: determining unit history dispatch data associated with a unit area based on the unit area information; determining a unit allocation proportion of the dispatch object based on the unit history dispatch data.

In some embodiments, the dispatch task data includes unit area data, and the determining the dispatch task allocation time and the dispatch task allocation quantity of the dispatch object based on the time of arrival of the transport object at the logistics node, the dispatch task data, and the allocation ratio includes: determining unit dispatch task data based on the unit area data; and determining the distribution quantity of the dispatch tasks of the dispatch object based on the unit dispatch task data and the unit distribution proportion.

In some embodiments, the historically assigned dispatch data includes shift information and unit area information, and the determining an allocation proportion of dispatch objects based on the historically assigned dispatch data includes: determining unit shift history dispatching data based on the shift information and the unit area information; determining a unit shift allocation proportion of the dispatch object based on the unit shift history dispatch data.

In some embodiments, the dispatch task data includes unit area data, and the determining the dispatch task allocation time and the dispatch task allocation quantity of the dispatch object based on the time of arrival of the transport object at the logistics node, the dispatch task data, and the allocation ratio includes: acquiring shift data of the logistics nodes; determining the shift of the transportation object to the logistics node based on the shift data of the logistics node and the time of the transportation object to the logistics node; determining unit dispatch task data based on the unit area data; and determining the dispatching task distribution quantity of the dispatching object based on the shift of the transportation object to the logistics node, the unit dispatching task data and the unit shift distribution proportion.

In some embodiments, the determining the dispatch task allocation time and the dispatch task allocation quantity of the dispatch object based on the time of arrival of the transport object at the logistics node, the dispatch task data, and the allocation proportion comprises: acquiring shift data of the logistics nodes; determining the shift of the transportation object to the logistics node based on the shift data of the logistics node and the time of the transportation object to the logistics node; and determining dispatching task allocation time of the dispatching object based on the shift of the transportation object to the logistics node.

In another aspect, the present application provides an apparatus for distributing dispatch tasks, the apparatus comprising: the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring logistics data associated with a transportation object, and the logistics data comprises position information of the transportation object and dispatching task data associated with a logistics node; the second acquisition module is used for acquiring dispatching data historically distributed by the logistics nodes; the prediction module is used for predicting the time when the transportation object reaches the logistics node based on the position information of the transportation object; the proportion determining module is used for determining the distribution proportion of the dispatching objects based on the dispatching data of the historical distribution; and the distribution module is used for determining the distribution time and the distribution quantity of the dispatching tasks of the dispatching objects based on the time of the transportation objects reaching the logistics nodes, the dispatching task data and the distribution proportion.

In another aspect, the present application further provides a system for distributing dispatch tasks, the system comprising:

one or more processors;

a memory; and

one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the method of assigning dispatch tasks.

In another aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, the computer program being loaded by a processor to perform the steps of the method for allocating dispatch tasks.

According to the method and the system, the dispatching task distribution quantity and the dispatching task distribution time of the dispatching object (such as the courier) are predicted through the logistics information and the logistics node data, the dispatching object can conveniently and reasonably arrange the dispatching path and the dispatching tool according to the dispatching task distribution quantity and the dispatching task distribution time corresponding to the predicted shift information, the work efficiency of the dispatching object is improved, and the dispatching cost of the dispatching tool is reduced.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

FIG. 1 is a schematic diagram of a scenario of an application system for assigning dispatch tasks according to an embodiment of the present application;

FIG. 2 is a schematic flow chart diagram illustrating a method for assigning dispatch tasks according to an embodiment of the present application;

FIG. 3 is a schematic flow chart illustrating a method for predicting the arrival time of a transportation object at a logistics node according to an embodiment of the present disclosure;

FIG. 4 is a flow chart illustrating a process of determining the number of dispatch tasks according to an embodiment of the present application;

FIG. 5 is another flow chart illustrating the determination of the allocated number of dispatch tasks according to an embodiment of the present disclosure;

FIG. 6 is a further flowchart illustrating a process of determining the number of dispatch tasks according to an embodiment of the present application;

FIG. 7 is a flowchart illustrating a process of determining dispatch task allocation time according to an embodiment of the present application;

FIG. 8 is a block diagram illustrating an exemplary embodiment of an apparatus for distributing dispatch tasks according to an exemplary embodiment of the present disclosure;

fig. 9 is a schematic structural diagram of an embodiment of a system for distributing dispatch tasks provided in the embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 invention.

In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention. Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.

In this application, the word "exemplary" is used to mean "serving as an example, instance, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is presented to enable any person skilled in the art to make and use the invention. In the following description, details are set forth for the purpose of explanation. It will be apparent to one of ordinary skill in the art that the present invention may be practiced without these specific details. In other instances, well-known structures and processes are not shown in detail to avoid obscuring the description of the invention with unnecessary detail. Thus, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.

Embodiments of the present application provide a method, an apparatus, a server, and a storage medium for distributing and dispatching tasks, which are described in detail below.

Fig. 1 is a schematic view of a scenario of an application system for assigning dispatch tasks in an embodiment of the present application.

The task allocation and dispatch application system can be a pre-estimation system applied to the task allocation and dispatch quantity distribution so as to facilitate the dispatch of objects to carry out reasonable work arrangement. For example, the task distribution and delivery application system can be used in the express industry to predict the time when an express transport vehicle arrives at an express site and predict the number of express to be distributed to couriers; for another example, the distribution task application system can predict the location where the logistics vehicle arrives at the logistics distribution center and the number of the transportation items distributed to the logistics distribution center transportation vehicle in the logistics industry; as another example, the distribution assignment task application system may apply commodity distribution to predict the arrival time of the commodity and the quantity of the commodity to be distributed to the store. It should be noted that the application scenario of the task assignment application system is only an illustrative example, and besides, the task assignment application system can be used for assigning tasks in various industries such as economy, culture, education, medical treatment, public management, and the like.

In some embodiments, the assignment tasking application may include a server 110, a network 120, a storage device 130, an assignment terminal 140, and a transport object 150. In some embodiments, the assignment dispatch task application system may predict dispatch task assignment times and dispatch task assignment quantities for dispatch objects (e.g., couriers, takeoffs, express robots, express drones, etc.) by obtaining logistics data and dispatch data from historical assignments of logistics nodes.

The server 110 may process data and/or information from at least one component of the task assigning application system or external data sources (e.g., the storage device 130, the assigning terminal 140, and the transportation object 150), for example, the server 110 may obtain historical assigned dispatching data of the logistics node from the storage device 130 to determine an assignment proportion of the transportation object, and for example, the server 110 may obtain real-time logistics information from the transportation object 150 to estimate the arrival time of the transportation object 150. In some embodiments, the server 110 may be a single server or a group of servers. The server group may be a centralized server group connected to the network 120 via an access point, or a distributed server group respectively connected to the network 120 via at least one access point. In some embodiments, server 110 may be connected locally to network 120 or remotely from network 120. For example, server 110 may access information and/or data stored in storage device 130 via network 120. In some embodiments, the server 110 may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-tiered cloud, and the like, or any combination thereof.

Network 120 connects the components of the tasking application system so that communications can be made between the components to facilitate the exchange of information and/or data. In some embodiments, at least one component in the assignment tasking application (e.g., server 110, storage device 130, assignment terminal 140, transport object 150) may send information and/or data (e.g., historically assigned dispatch data) to other components in the assignment tasking application via network 120. In some embodiments, the network between the parts in the assignment tasking application system may be any one or more of a wired network or a wireless network. For example, Network 120 may include a cable Network, a wired Network, a fiber optic Network, a telecommunications Network, an intranet, the internet, a Local Area Network (LAN), a Wide Area Network (WAN), a Wireless Local Area Network (WLAN), a Metropolitan Area Network (MAN), a Public Switched Telephone Network (PSTN), a Bluetooth Network (Bluetooth), a ZigBee (ZigBee), Near Field Communication (NFC), an intra-device bus, an intra-device line, a cable connection, and the like, or any combination thereof. The network connection between each two parts may be in one of the above-mentioned ways, or in a plurality of ways.

Storage device 130 may store data and/or instructions. In some embodiments, the storage device 130 may store data obtained from the dispensing terminal 140, such as dispatch task data. As another example, the storage device 130 may store historical logistics data of the transported object 150. In some embodiments, storage device 130 may store data and/or instructions that server 110 may execute. In some embodiments, storage 130 may include mass storage, removable storage, volatile read-write memory, read-only memory (ROM), and the like, or any combination thereof. Exemplary mass storage devices may include magnetic disks, optical disks, solid state disks, and the like. Exemplary removable memory may include flash drives, floppy disks, optical disks, memory cards, compact disks, magnetic tape, and the like. Exemplary volatile read-write Memory can include Random Access Memory (RAM). Exemplary RAMs may include Dynamic Random Access Memory (DRAM), Double-Data-Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Static Random Access Memory (SRAM), Thyristor Random Access Memory (T-RAM), Zero Capacitance Random Access Memory (Z-RAM), and the like. Exemplary Read-Only memories may include mask Read-Only Memory (MROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (pemrom), Electrically Erasable Programmable Read-Only Memory (EEPROM), Compact Disc Read-Only Memory (CD-ROM), digital versatile disk Read-Only Memory (dvd-ROM), and the like. In some embodiments, storage device 130 may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-tiered cloud, and the like, or any combination thereof.

The distribution terminal 140 may receive the dispatch task allocation time and the dispatch task allocation amount sent by the server 110. In some embodiments, the distribution terminal 140 may be a device having information receiving and/or transmitting capabilities to facilitate transmission to the server 110 for processing. In some embodiments, the owner of the dispensing terminal 140 may be a worker, such as a courier, a takeout person, a delivery person, or the like. In some embodiments, the dispensing terminal 140 may be an executor, such as a courier robot, a courier drone, a vehicle terminal, and the like. In some embodiments, the dispensing terminal 140 may include a plurality of

terminals

141, 142, 143. For example, the distribution terminal 140 may include a mobile device 141, a tablet computer 142, a laptop computer 143, a drone 144, the like, or any combination thereof.

The transport object 150 may issue logistics data to the server 110, where the logistics data includes the real-time location of the transport object 150. In some embodiments, the transport object 150 may have information receiving and/or transmitting functionality. In some embodiments, the object 150 is transported. In some embodiments, the transported object 150 may be an airborne transportation device, such as an airplane, a flying automobile, a flying boat, or the like. In some embodiments, the transportation object 150 may also be a surface transportation device, such as a ship, an amphibious vehicle, or the like. In some embodiments, the transport object 150 may also be a transport device having one or more wheel structures. In some embodiments, the transportation object 150 may also be a land transportation device, such as an automobile, a van, a tricycle, a motorcycle, or the like.

It should be noted that the above description of the assignment task application system is for purposes of example and illustration only and does not limit the scope of applicability of the present application. For example, the assignment task application system may further include a terminal device communicating with a logistics site (e.g., a courier site) to facilitate obtaining site information.

As shown in fig. 2, a flowchart of an embodiment of a method for assigning a dispatch task in an embodiment of the present application is shown, where the method for assigning a dispatch task includes:

step S201, obtaining logistics data associated with a transportation object, wherein the logistics data comprises position information of the transportation object and dispatching task data associated with logistics nodes.

A delivery object may refer to an object that completes an assignment task (e.g., a courier). In some embodiments, the delivery subject may be a courier, a courier robot, a courier drone, a transport vehicle driven by a courier, a delivery person delivering goods to a store, and the like.

The logistics node may refer to a location where the transported goods of the transportation object are distributed to be delivered to the next step, where the next step may be express delivery, store goods delivery, factory material delivery, and the like. In some embodiments, the logistics node may refer to a logistics hub, an express delivery site, a commodity distribution site, and the like.

The delivery job data associated with the logistics node may refer to delivery data (e.g., courier) to be delivered to the logistics node (e.g., courier site) for further delivery. In some embodiments, the delivery task data associated with the logistics node may include a courier order number, a site number associated with the logistics node, a type of courier, a weight of the courier, a delivery location, and the like.

The logistics data associated with the transportation object may refer to data information related to the transportation of the transportation object. In some embodiments, logistics data associated with a transportation object may include location information of the transportation object and dispatch task data associated with a logistics node. In some embodiments, the location information of the transported object may be determined by a positioning technique, such as GPS. In some embodiments, the location information of the transportation object may be determined by the origin (e.g., logistics hub) when the transportation object is sent to the server 110.

In some embodiments, such as embodiments in which the location information of the transportation object is sent from the origin to the server 110, the obtaining of the logistics data associated with the transportation object may be obtaining the location information of the transportation object and the delivery task data associated with the logistics node from the storage device 130. In some embodiments, such as embodiments where the location information of the transportation object is determined by a positioning technique, obtaining logistics data associated with the transportation object may be obtaining dispatch task data associated with the logistics node from the storage device 130, and obtaining the location information of the transportation object by a positioning technique (e.g., GPS).

Step S202, predicting the time of the transportation object reaching the logistics node based on the position information of the transportation object.

After the position information of the transportation object is obtained, the time when the transportation object reaches the logistics node can be predicted based on the position information of the transportation object, so that the time when the dispatching task is to be allocated to the dispatching object can be determined. In some embodiments of the application, the time of the transportation object reaching the logistics node may be predicted in a machine learning manner, for example, historical logistics information is used as training data, a machine learning model parameter is trained to obtain a trained machine learning model, and then the time of the transportation object reaching the logistics node is predicted through the position information of the transportation object and the trained machine learning model. The machine learning model can be a convolutional neural network, a decision tree, a random forest, a cyclic neural network, a support vector machine, a Markov model, and the like. In some other embodiments of the present application, the time of arrival of the transportation object at the logistics node is predicted to be determined by calculating historical average arrival time through historical logistics data. Specifically, with respect to calculating the historical average arrival time according to the historical logistics data, the time for predicting the transportation object to arrive at the logistics node can be seen in fig. 3, and steps S301 to S304.

And step S203, obtaining dispatch data historically distributed by the logistics nodes.

The historically assigned delivery data may refer to the delivery task (e.g., courier) data assigned to the delivery object (e.g., courier) in the past distribution history, wherein the historically assigned delivery data may include a courier number, courier information of the delivery, and the like. In some embodiments, historically assigned delivery data may also include a site number, a type of courier, a weight of the courier, a delivery location, unit area information, and the like associated with the logistics node. Specifically, obtaining dispatch data of the logistics node historical allocation may be performed by the server 110. In some embodiments, the dispatch data that the server 110 obtains the distribution history of the logistics node may be obtained from the storage device 130.

Step S204, determining the distribution proportion of the dispatch objects based on the dispatch data of the historical distribution.

The allocation ratio of the dispatch object may refer to an allocation ratio value allocated to the dispatch object dispatch task. In some specific embodiments, the distribution ratio of the dispatch objects may be determined according to a distribution ratio corresponding to dispatch data historically distributed by the logistics node, for example, the distribution ratio of the dispatch objects is calculated according to dispatch data historically distributed by the logistics node in the last month, and for example, the distribution ratio of the dispatch objects is calculated according to dispatch data historically distributed by the logistics node in the last week.

In some embodiments of the present application, to determine the distribution ratio accurately for dispatch objects in dispatch shifts, the determined distribution ratio may be a shift distribution ratio associated with the dispatch object shift, where the shift may refer to the work schedule of the logistics node, e.g., one shift from 9 am to 12 pm, and 1 pm to 3 pm and 4 pm to 6 pm. Specifically, the shift allocation ratio may be determined in fig. 4, steps S401 to S405. In some other embodiments of the present application, in order to determine the allocation ratio for the dispatch target according to the dispatch unit area, the determined allocation ratio may be a unit allocation ratio associated with the unit area, wherein the unit area may refer to a divided dispatch area, such as a street, an administrative area, a township, a cell, a square, and the like. Specifically, the determination of the unit allocation ratio may be referred to fig. 5, steps S501 to S504. In some other embodiments of the present application, in order to accurately determine the distribution ratio for the dispatch target according to the dispatch shift and the dispatch unit area, the determined distribution ratio may also be a unit shift distribution ratio associated with the shift and the unit area, and specifically, the step S601 to step S606 may be referred to in fig. 6.

Step S205, determining dispatching task distribution time and dispatching task distribution quantity of the dispatching object based on the time of the transportation object reaching the logistics node, the dispatching task data and the distribution proportion.

Dispatch task allocation time may refer to the time when a dispatch object receives or receives a task. In some embodiments of the present application, the dispatch task allocation time for the dispatch object may be determined by the arrival time of the transportation object at the logistics node, for example, if the arrival time of the transportation object at the logistics node is 14:20, then the dispatch task allocation time for the dispatch object may be determined to be 14: 20. In other embodiments of the present application, the dispatch task allocation time of the dispatch object may be determined according to a time delay after the transportation object arrives at the logistics node, for example, the time when the transportation object arrives at the logistics node is 14:20, and the dispatch task allocation time of the dispatch object may be determined to be 14:40 after 20 minutes. In other embodiments of the present application, determining the dispatch task allocation time of the dispatch object may also be determined by comparing the arrival time of the transportation object at the logistics node with the shift ratio of the logistics node, so as to refine the allocation time and arrange according to the working time rule of the logistics node. Specifically, the step of determining the dispatch task allocation time of the dispatch object according to the ratio of the arrival time of the transportation object at the logistics node to the shift number of the logistics node can be seen in fig. 7 and steps S701 to S703.

The dispatch task allocation number may refer to the number of tasks received or received by the dispatch object. In some embodiments of the present application, determining the distribution amount of the delivery tasks of the delivery object may be determined by the delivery task data delivered by the transportation object to the logistics node and the distribution ratio, for example, if a truck delivers 300 deliveries to a certain delivery site together, and the distribution ratio of courier a at the delivery site is 0.2, it may be determined that the distribution ratio of courier a at this time is 60. In some other embodiments of the present application, in order to accurately determine the task allocation of the shift condition, the dispatch task allocation amount for determining the dispatch object may be determined by the shift allocation ratio, and specifically, see fig. 4, steps S401 to S405 for determining the dispatch task allocation amount for determining the dispatch object by the shift allocation ratio. In some embodiments of the present application, in order to refine the task allocation of the unit area case, the dispatch task allocation number for determining the dispatch object may be determined by the unit allocation ratio, and in particular, see fig. 5, steps S501 to S504, for determining the dispatch task allocation number for determining the dispatch object by the unit allocation ratio. In some embodiments of the present application, in order to refine the task allocation of the unit area and the number of the dispatch tasks, the dispatch task allocation amount for determining the dispatch object may be determined by the unit shift allocation ratio, and in particular, see fig. 6, steps S601 to S606 for determining the dispatch task allocation amount for determining the dispatch object by the unit shift allocation ratio.

In some embodiments of the present application, the dispatch task allocation number and the dispatch task allocation time may be determined simultaneously and sent to the dispatch object simultaneously. In other embodiments of the present application, the allocation amount of the dispatching tasks may be determined first, then the allocation time of the dispatching tasks is determined, and then the dispatching tasks are sent to the dispatching objects according to the determined sequence.

It should be noted that the above is intended to clearly illustrate the verification process of the present application, and the steps S201 and S203 may be executed simultaneously to obtain dispatch data of historical distribution and logistics data associated with a transportation object, for example, without any specific limitation on the order of steps implemented in the present application.

Fig. 3 is a schematic flow chart illustrating a process of predicting the arrival time of a transportation object at a logistics node according to an embodiment of the present application. The predicting of the arrival time of the transportation object at the logistics node may include steps S301 to S303, which are specifically as follows:

step S301, obtaining historical logistics data related to the position information of the transportation object.

The historical logistics data may refer to past transportation data information (for example, logistics data before the target time period with respect to the logistics data of step S201) of the transportation object, wherein the transportation data information may include a transportation route, a departure time, a departure point, a passing point time, a final arrival point, a final arrival time, and the like. The historical logistics data associated with the position information of the transportation object may refer to historical logistics data of which the transportation route includes position information of the transportation object, for example, the starting point of the historical logistics data is the same as the position information of the transportation object; for another example, a certain passing point of the historical logistics data is the same as the position information of the transportation object. In some specific embodiments, the obtaining of the historical logistics data associated with the position information of the transportation object may be receiving the historical logistics data sent by the storage device 130.

Step S302, determining historical average arrival time of the transportation object to the logistics node based on the historical logistics data.

The historical average arrival time of the transportation object at the logistics node may refer to an average time (e.g., 3 hours, 50 minutes, etc.) for the transportation object to arrive at the logistics node from the current position (departure place or a certain place in the way) in the historical logistics data.

To facilitate determining a more accurate historical average arrival time, in some specific embodiments, the historical logistics data may include a historical departure time, a historical departure location, a historical arrival time, a historical arrival location, and the like, and determining the historical average arrival time of the transportation object at the logistics node may include: determining correlated historical logistics data based on the historical logistics data, wherein a historical departure place of the correlated historical logistics data is correlated with the position information of the transportation object, and a historical arrival place of the correlated historical logistics data is correlated with the logistics node; determining a historical average arrival time based on the correlated historical logistics data. In the above embodiment, the association between the historical departure point and the position information of the transportation object may mean that the historical departure point and the position information of the transportation object are the same; the historical arrival place is associated with the logistics node, namely the historical arrival place is the same as the logistics node, and more accurate historical average arrival time is determined through the associated historical logistics data of the same departure place and the same arrival place.

In some embodiments of the present application, the historical average arrival time of the transportation object at the logistics node may be determined as a statistical average method, for example, if the historical logistics data includes { data 1, origin a, arrival B, time spent 4 hours }, { data 2, origin a, arrival B, time spent 2 hours }, { data 3, origin a, arrival B, time spent 3 hours }, { data 4, origin a, arrival B, time spent 9 hours }, then the historical average arrival time of the transportation object at the logistics node may be determined as 4 hours and 30 minutes. In other embodiments of the present application, the historical average arrival time of the transportation object at the logistics node may be determined by removing abnormal data, and then determining based on a statistical average method, for example, for the historical logistics data, data 4 with a time consumption much higher than other historical logistics data may be removed, and then the historical average arrival time of the transportation object at the logistics node may be obtained by statistics, and may be 3 hours.

After determining the historical average arrival time of the transportation object at the logistics node, the historical average arrival time may be stored in the storage device 130, so as to predict the arrival time of the transportation object at the logistics node each time for obtaining the historical average arrival time. In some specific embodiments, such as the embodiment that stores the historical average arrival time in the storage device 130, the historical average arrival time may also be updated at intervals to facilitate determining a more accurate historical average arrival time.

It should be noted that the above-mentioned manner for determining the historical average arrival time of the transportation object at the logistics node based on the historical logistics data is only an example, and the historical average arrival time may also be obtained based on other mathematical statistics manners, for example, a manner of data statistics such as normal distribution, mean square deviation, and the like.

Step S303, obtaining the historical average arrival time of the transportation objects arriving at the distribution station.

In some embodiments of the present application, obtaining the historical average arrival time may be receiving data sent by storage device 130. In other embodiments of the present application, the historical average arrival time may be obtained by direct calculation, for example, according to the above step S302, so as to obtain the historical average arrival time determined according to the latest data.

And S304, predicting the time of the transportation object reaching the logistics node based on the historical average arrival time.

Predicting the time at which the transport object arrives at the logistics node may refer to a predicted time point or a range value of the predicted time at which the transport object arrives at the logistics node. In some embodiments of the present application, the prediction of the arrival of the transportation object at the logistics node may be a determined value, for example, the predicted arrival time is 16 o' clock afternoon. In other embodiments of the present application, the time for predicting the transportation object to arrive at the logistics node may be a range of values, for example, the predicted arrival time is between 15 pm 50 minutes and 16 pm 10 minutes.

After the historical average arrival time of the transportation object reaching the logistics node is determined according to the historical logistics data, the arrival time of the transportation object reaching the logistics node can be predicted. In some embodiments of the present application, predicting the arrival time of the transportation object at the logistics node may directly sum the current time with the historical average arrival time, for example, if it is determined from the historical logistics data that the historical average arrival time of the transportation object at the logistics node is 2 hours and the current time is 14 pm, then the arrival time of the transportation object at the logistics node may be predicted to be 16 pm. In other embodiments of the present application, the time for predicting the arrival of the transportation object at the logistics node may be directly obtained by summing the current time and the historical average arrival time, and then extending forward or backward for a period of time, for example, if the historical average arrival time for the transportation object to arrive at the logistics node is determined to be 2 hours according to the historical logistics data, and the current time is 14 pm, the time for the transportation object to arrive at the logistics node may be predicted to be between 15 pm 50 minutes and 16 pm 10 minutes.

It should be noted that the above description regarding predicting the arrival time of the transportation object at the logistics node is only exemplary, and for example, the prediction of the arrival time of the transportation object at the logistics node may be further refined based on the error value of the past arrival at the logistics node.

Fig. 4 is a schematic flow chart illustrating the process of determining the distribution quantity of dispatch tasks according to the embodiment of the present application. In some embodiments, historically assigned dispatch data includes shift information to facilitate determining assignment proportions associated with shifts based on the shift information. Specifically, determining the distribution number of the dispatching tasks may include steps S401 to S405 as follows:

and S401, acquiring the shift data of the logistics nodes.

The shift may refer to the work schedule of the logistics node, for example, one shift may be located from 9 am to 12 pm, and two shifts may be located from 1 pm to 3 pm, and from 4 pm to 6 pm. For another example, 8 hours of operation per day may be divided into 8 shifts. In some embodiments of the present application, the shift may be fixedly arranged by the logistics node, so as to facilitate the unified management of the logistics node. In other embodiments of the present application, the shift may be scheduled by the dispatch object itself, so that the dispatch object can schedule the work time appropriately.

In some particular embodiments, such as for embodiments where the shift is a fixed arrangement of logistics nodes, the server 110 may receive the shift data that the storage device 130 sends in association with the logistics nodes. In some other specific embodiments, such as for the embodiment where the shift is the dispatch subject's own arrangement, the server 110 may receive the shift data sent by the terminal device held by the dispatch subject.

Step S402, determining the shift of the transportation object to the logistics node based on the shift data of the logistics node and the time of the transportation object to the logistics node.

After the shift data of the logistics node is obtained, the shift of the transportation object reaching the logistics node can be determined by combining the time of the transportation object reaching the logistics node, so that the shift allocation proportion associated with the delivery object can be determined. In some embodiments of the present application, the shift determined that the transportation object arrives at the logistics node may be a shift at which the transportation object arrives at the logistics node, for example, the time that the transportation object arrives at the logistics node is 10 minutes at 16 pm, and the shift determined that the transportation object arrives at the logistics node may be a shift from 16 pm to 17 pm. In some other embodiments of the present application, the shift determined that the transportation object arrives at the logistics node may be the previous or next shift at which the transportation object arrives at the logistics node, for example, the time that the transportation object arrives at the logistics node is 10 minutes at 16 pm, and the shift determined that the transportation object arrives at the logistics node may be a shift from 15 pm to 16 pm.

Step S403, determining the historical dispatch data of the shift related to the arrival time of the transportation object at the logistics node based on the shift information.

To determine the shift allocation proportion of dispatch objects, shift history dispatch data associated with the arrival time of the transportation objects at the logistics node may be determined based on the shift information.

In some embodiments of the present application, the historical dispatch data of the shift may be determined statistically from the dispatch data of the historical allocation of the arrival time of the transportation object at the logistics node in the same shift, for example, the arrival time of the transportation object at the logistics node is shift 1, and for the dispatch data of the historical allocation { historical dispatch data 1, dispatch object a, shift 1, allocation example 1, cycle 1}, { historical dispatch data 2, dispatch object a, shift 2, allocation example 2, cycle 2}, { historical dispatch data 3, dispatch object a, shift 1, allocation example 3, and cycle 3}, it may be determined that the historical dispatch data of the shift for dispatch object a, shift 1, and historical dispatch data 2.

In some further embodiments of the present application, determining the historical dispatch data for the shift may be statistically determined from dispatch data assigned historically for neighboring shifts of the arrival time of the transportation object at the logistics node, for example, for the dispatch data assigned historically described above, it may be determined that the historical dispatch data for dispatch object a, shift 1, includes historically assigned dispatch data 1, historically assigned dispatch data 2, and historically assigned dispatch data 3.

Step S404, determining the distribution proportion of the shift of the dispatch object based on the shift history dispatch data.

The shift distribution proportion can be the distribution proportion associated with the shift information of the logistics nodes so as to realize dispatch task distribution of shift fineness. In some embodiments of the present application, determining the shift allocation ratio may refer to a ratio obtained by statistically averaging the allocation ratios in the shift history dispatch data, for example, for the shift history dispatch data { the history allocated dispatch data 1, dispatch object a, shift 1, 0.3, cycle 1}, { the history allocated dispatch data 2, dispatch object a, shift 2, 0.2, cycle 2}, { the history allocated dispatch data 3, dispatch object a, shift 1, 0.4, cycle 3}, it may be determined that the shift allocation ratio is 0.3. In some other embodiments of the present application, determining the assignment proportion of the shift may also be a proportion obtained by mathematically statistically (e.g., just too distributed) processing the assignment proportion in the shift history dispatch data.

Step S405, determining the distribution quantity of the dispatching tasks of the dispatching objects based on the number of the shifts of the transportation objects reaching the logistics nodes and the distribution proportion of the number of the shifts.

After the shift of the transportation object reaching the logistics node and the shift allocation proportion are determined, the dispatching task allocation quantity of the dispatching object can be determined by combining the dispatching task data. In some embodiments of the present application, the determining of the assigned number of the dispatch tasks of the dispatch object may be obtained by multiplying the assignment proportion of the number of times of the dispatch object by the data of the dispatch task, for example, if the assigned number of times of the dispatch task is 300, and the assignment proportion of the number of times of the dispatch object a is 0.1, the assigned number of the dispatch tasks of the dispatch object a may be determined to be 30. In some other embodiments of the present application, the number obtained by multiplying the shift allocation ratio of the delivery object by the data of the delivery task may be further subjected to floating up or floating down, for example, for the 300-piece express delivery, if the shift allocation ratio of the delivery object a is 0.1, the number of the delivery tasks allocated to the delivery object a may be determined to be 20-piece express delivery or 40-piece express delivery, so that the number of the delivery tasks allocated according to the determination may be adjusted according to other influence factors (for example, the next shift leave).

It should be noted that the above-mentioned sequence of the steps S401 to S405 for determining the distribution quantity of the dispatching tasks is not limited, and for example, the steps S403 and S404 may be executed first to determine the distribution ratio of the shift, and then the steps S401 and S402 may be executed to determine the shift of the transportation object reaching the logistics node.

Fig. 5 is another schematic flow chart of determining the allocated number of dispatch tasks according to the embodiment of the present application. In some embodiments, dispatch data for historical assignments includes cell region information to facilitate determining assignment ratios associated with cell regions based on the cell region information. Specifically, the determining the distribution number of the dispatching tasks may include steps S501 to S504, which are specifically as follows:

step S501, unit history dispatch data associated with the unit area is determined based on the unit area information.

The unit area may refer to a divided delivery area such as a street, an administrative area, a town, a cell, a square, and the like. In order to determine the allocation information related to the unit area and achieve accurate allocation of the unit area subdivision region, in some embodiments of the present application, the unit history dispatch data associated with the unit area may be determined based on the unit area information.

In some embodiments of the present application, determining unit historical dispatch data may be to count data with the same distribution area in historically distributed dispatch data, for example, for { historically distributed dispatch data 1, dispatch object a, distribution area 1, distribution ratio 1, period 1}, { historically distributed dispatch data 2, dispatch object a, distribution area 2, distribution ratio 2, period 2}, { historically distributed dispatch data 3, dispatch object a, distribution area 1, distribution ratio 3, and period 3}, it may be determined that historically distributed dispatch data 1 and historically distributed dispatch data 3 are unit historical dispatch data of dispatch object a. In other embodiments of the present application, determining unit historical dispatch data may be to unify data of similar distribution areas in the dispatch data of historical distribution, for example, for the dispatch data of historical distribution, since the distribution area 1 is adjacent to the distribution area 2, the dispatch data 1 of historical distribution, the dispatch data 2 of historical distribution, and the dispatch data 3 of historical distribution may be determined as unit historical dispatch data of the dispatch object a.

Step S502, the unit distribution proportion of the dispatch object is determined based on the unit history dispatch data.

After the unit history dispatch data is determined, the unit allocation proportion of the dispatch object can be determined according to the unit history dispatch data, wherein the unit allocation proportion can be the allocation proportion associated with the unit area, so that the dispatch quantity allocation of the unit area is realized. In some embodiments of the present application, determining the unit allocation ratio may be a ratio statistically averaged over allocations ratios in the unit history dispatch data. In some other embodiments of the present application, determining the unit distribution ratios may be a ratio obtained by mathematically statistically (e.g., positively distributed) processing the distribution ratios in the unit history dispatch data.

Step S503, determining unit dispatch task data based on the unit area data.

For dispatch task allocation per unit area, unit dispatch task data may be determined based on the unit area data, where the unit dispatch task data may be data of the same or similar unit areas in the dispatch task data. In some embodiments of the present application, determining unit dispatch task data may be determined by unifying data of the same unit area. In some other embodiments of the present application, determining unit dispatch task data may be determined by unifying data adjacent to the unit area.

Step S504, based on the unit dispatch task data and the unit allocation proportion, determining the dispatch task allocation quantity of the dispatch object.

After the unit dispatching task data and the unit distribution proportion are determined, the dispatching task distribution quantity of the dispatching object can be determined, and task distribution of unit area fineness is achieved.

In some embodiments of the present application, the determination of the assigned number of tasks for dispatch of the dispatch object may be obtained by multiplying the unit dispatch task data of the dispatch object by the unit allocation ratio, for example, if the assigned number of tasks for dispatch of unit area a is 300, and the unit allocation ratio of dispatch object a is 0.3, then the assigned number of tasks for dispatch object a may be determined to be 90. In some other embodiments of the present application, the number obtained by multiplying the unit allocation proportion of the delivery object by the unit delivery task data may be further subjected to floating-up or floating-down processing, for example, for 300 pieces of express delivery in the unit area a, the unit allocation proportion of the delivery object a is 0.3, and the distribution number of the delivery tasks of the delivery object a may be determined to be 80 pieces of express delivery or 100 pieces of express delivery, so that the distribution number of the delivery tasks may be adjusted according to other influence factors (area a rainstorm).

It should be noted that the above-mentioned order of the steps S501 to S504 for determining the distribution amount of the dispatching task is not restrictive, and for example, the step S503 of determining the unit dispatching task data may be executed first, and then the step S501 and the step S502 of determining the distribution ratio of the unit may be executed.

Fig. 6 is a further flowchart illustrating the process of determining the distribution quantity of dispatch tasks according to the embodiment of the present application. In some embodiments, historically assigned dispatch data includes shift information and unit area information to facilitate determining assignment proportions associated with unit areas, shifts, based on the shift information and the unit area information. Specifically, the determining the distribution number of the dispatching tasks may include steps S601 to S606, which are specifically as follows:

and S601, acquiring the shift data of the logistics nodes.

The shift may refer to the work schedule of the logistics node. In some particular embodiments, such as for embodiments where the shift is a fixed arrangement of logistics nodes, the server 110 may receive the shift data that the storage device 130 sends in association with the logistics nodes. In some other specific embodiments, such as for the embodiment where the shift is the dispatch subject's own arrangement, the server 110 may receive the shift data sent by the terminal device held by the dispatch subject.

Step S602, determining the shift of the transportation object to the logistics node based on the shift data of the logistics node and the time of the transportation object to the logistics node.

After the shift data of the logistics node is obtained, the shift of the transportation object reaching the logistics node can be determined by combining the time of the transportation object reaching the logistics node, so that the shift allocation proportion associated with the delivery object can be determined.

In some embodiments of the present application, the shift determined that the transportation object arrives at the logistics node may be a shift at which the transportation object arrives at the logistics node, for example, the time that the transportation object arrives at the logistics node is 10 minutes at 16 pm, and the shift determined that the transportation object arrives at the logistics node may be a shift from 16 pm to 17 pm. In some other embodiments of the present application, the shift determined that the transportation object arrives at the logistics node may be the previous or next shift at which the transportation object arrives at the logistics node, for example, the time that the transportation object arrives at the logistics node is 10 minutes at 16 pm, and the shift determined that the transportation object arrives at the logistics node may be a shift from 15 pm to 16 pm.

Step S603, determining unit dispatch task data based on the unit area data.

In some embodiments of the present application, determining unit historical dispatch data may be to unify data with the same allocation region in historically allocated dispatch data, for example, for { historically allocated dispatch data 1, dispatch object a, allocation region 1, allocation ratio 1, period 1}, { historically allocated dispatch data 2, dispatch object a, allocation region 2, allocation ratio 2, period 2}, { historically allocated dispatch data 3, dispatch object a, allocation region 1, allocation ratio 3, and period 3}, it may be determined that historically allocated dispatch data 1 and historically allocated dispatch data 3 are unit historical dispatch data of dispatch object a. In other embodiments of the present application, determining unit historical dispatch data may be to count data with similar distribution areas in the historically-distributed dispatch data, for example, for the historically-distributed dispatch data, since the distribution area 1 is adjacent to the distribution area 2, the historically-distributed dispatch data 1, the historically-distributed dispatch data 2, and the historically-distributed dispatch data 3 may be determined as unit historical dispatch data of the dispatch object a.

Step S604, unit shift history dispatch data is determined based on the shift information and the unit area information.

For dispatch task assignment by unit area, shift, unit shift history dispatch data may be determined based on the unit area data, where the unit shift history dispatch data may refer to data in the dispatch task data that have the same or similar unit areas and the same or similar shift. In some embodiments of the present application, determining the unit shift history dispatch data may be determined by unifying the unit region-identical, shift-identical data. In some other embodiments of the present application, the determination of the unit shift history dispatch data may be determined by unifying the unit area adjacent and shift adjacent data.

Step S605 determines the unit shift allocation ratio of the dispatch target based on the unit shift history dispatch data.

After the unit shift history dispatch data is determined, the unit shift allocation proportion of the dispatch object can be determined according to the unit shift history dispatch data, wherein the unit shift allocation proportion can be the allocation proportion associated with the unit area and the shift, so that the dispatch quantity allocation of the unit area and the shift is realized. In some embodiments of the present application, determining the unit shift allocation ratio may be a statistically averaged ratio of allocations in the unit shift history dispatch data. In some other embodiments of the present application, determining the unit distribution ratios may be a ratio obtained by mathematically statistically (e.g., just too distributed) processing the distribution ratios in the unit shift history dispatch data.

Step S606, determining the dispatching task distribution quantity of the dispatching objects based on the number of the transportation objects reaching the logistics node, the unit dispatching task data and the unit number distribution proportion.

After the unit dispatching task data, the number of the shifts of the transportation objects reaching the logistics node and the unit shift distribution proportion are determined, the dispatching task distribution quantity of the dispatching objects can be determined, and task distribution of unit areas and the shift fineness is achieved.

In some embodiments of the present application, the determination of the assigned number of dispatch tasks for the dispatch target may be obtained by multiplying the unit dispatch task data with the same shift as the dispatch target by the unit assignment proportion, for example, for the dispatch task assignment number of unit area a, shift 1 in the morning, being 100 express items, and the unit shift assignment proportion of dispatch target a being 0.2, the assigned number of dispatch tasks for dispatch target a may be determined to be 20 express items. In some other embodiments of the present application, the number obtained by multiplying the unit dispatch task data with the same shift as the dispatch target by the unit shift allocation proportion may be further subjected to floating or floating processing, for example, if the dispatch task allocation number of the unit area a in shift 1 in the morning is 100 express deliveries and the unit allocation proportion of the dispatch target a is 0.2, the dispatch task allocation number of the dispatch target a may be determined to be 30 express deliveries or 50 express deliveries, so that the dispatch task allocation number may be adjusted according to other influence factors (e.g., rainstorm in the area a, leave behind the next shift, etc.) according to the determination.

It should be noted that the above-mentioned order of the steps S601 to S506 for determining the distribution amount of the dispatching task is not limited, and for example, the step S603 of determining the dispatching task data, the steps S601 and S602 of determining the shift of the transportation object reaching the logistics node, and the steps S604 and S605 of determining the distribution ratio of the shift of the unit may be executed.

Fig. 7 is a flowchart illustrating a process of determining an allocation time of a dispatch task according to an embodiment of the present application. In some embodiments, determining dispatch task allocation times may be associated with logistics node shifts to facilitate allocation of tasks according to work shift schedules of logistics nodes. Specifically, the determining of the dispatch task allocation time may include steps S701 to S703, which are specifically as follows:

and step S701, acquiring the shift data of the logistics nodes.

Step S702, determining the shift of the transportation object to the logistics node based on the shift data of the logistics node and the time of the transportation object to the logistics node.

Step S703, determining the dispatch task allocation time of the dispatch object based on the shift of the transportation object reaching the logistics node.

After the shift of the transportation object reaching the logistics node is determined, the dispatching task allocation time of the dispatching object can be determined, so that the tasks can be allocated according to the work shift arrangement of the logistics node. In some embodiments of the present application, it may be determined that the dispatch task allocation time of the dispatch object is not available at a certain time of the shift in which the transportation object arrives at the logistics node, for example, for shift 2 (time range is 11 o 'clock to 12 o' clock) in which the transportation object arrives at the logistics node, 11 o 'clock may be used as the dispatch task allocation time of the dispatch object, and 11 o' clock 30 may also be used as the dispatch task allocation time of the dispatch object. In other embodiments of the present application, it may be determined that the dispatch task allocation time of the dispatch object is not determined at a certain time when the transportation object arrives at the adjacent shift of the logistics node, for example, for shift 2 (time range 11 to 12) when the transportation object arrives at the logistics node, 10 o' clock 30 of the previous shift may be used as the dispatch task allocation time of the dispatch object.

In order to better implement the method for distributing dispatch tasks in the embodiment of the present application, on the basis of the method for distributing dispatch tasks, an apparatus for distributing dispatch tasks is further provided in the embodiment of the present application, as shown in fig. 8, the method 800 for distributing dispatch tasks includes:

a first obtaining module 801, configured to obtain logistics data associated with a transportation object, where the logistics data includes location information of the transportation object and dispatch task data associated with a logistics node.

A second obtaining module 802, configured to obtain dispatch data historically allocated to the logistics node.

A predicting module 803, configured to predict, based on the location information of the transportation object, a time when the transportation object arrives at the logistics node.

A proportion determining module 804, configured to determine a distribution proportion of the dispatch object based on the dispatch data of the historical distribution.

The allocating module 805 is configured to determine the dispatch task allocation time and the dispatch task allocation number of the dispatch object based on the time when the transportation object arrives at the logistics node, the dispatch task data, and the allocation proportion.

In some embodiments of the present application, the prediction module 803 is specifically configured to:

acquiring historical logistics data associated with the position information of the transport object;

determining historical average arrival time of the transportation object to the logistics node based on the historical logistics data;

acquiring historical average arrival time of the transportation object reaching the logistics node;

and predicting the time of the transportation object reaching the logistics node based on the historical average arrival time.

In some embodiments of the present application, the dispatch data of the historical assignment includes shift information, and the proportion determining module 804 is specifically configured to:

determining the historical dispatch data of the shift related to the arrival time of the transportation object at the logistics node based on the shift information;

determining a shift allocation proportion of the dispatch object based on the shift history dispatch data.

In some other embodiments of the present application, the dispatch data of the historical allocation includes unit area information, and the proportion determining module 804 is specifically configured to:

determining unit history dispatch data associated with a unit area based on the unit area information;

determining a unit allocation proportion of the dispatch object based on the unit history dispatch data.

In some other embodiments of the present application, the dispatch data of the historical assignment includes shift information and unit area information, and the proportion determining module 804 is specifically configured to:

determining unit shift history dispatching data based on the shift information and the unit area information;

determining a unit shift allocation proportion of the dispatch object based on the unit shift history dispatch data.

In some embodiments of the present application, the assignment module 805 is specifically configured to:

acquiring shift data of the logistics nodes;

determining the shift of the transportation object to the logistics node based on the shift data of the logistics node and the time of the transportation object to the logistics node;

and determining the dispatching task distribution quantity of the dispatching object based on the shift of the transportation object reaching the logistics node and the shift distribution proportion.

In some other embodiments of the present application, the allocating module 805 is specifically configured to:

determining unit dispatch task data based on the unit area data;

and determining the distribution quantity of the dispatch tasks of the dispatch object based on the unit dispatch task data and the unit distribution proportion.

In some embodiments of the present application, the allocating module 805 is specifically configured to:

acquiring shift data of the logistics nodes;

determining unit dispatch task data based on the unit area data;

and determining the dispatching task distribution quantity of the dispatching objects based on the shift of the transportation objects to the logistics nodes, the unit dispatching task data and the unit shift distribution proportion.

acquiring shift data of the logistics nodes;

and determining dispatching task allocation time of the dispatching object based on the shift of the transportation object to the logistics node.

The device of distributing the dispatch task in this application goes to predict dispatch object's dispatch task distribution quantity and dispatch task distribution time through logistics information and logistics node data, and the dispatch object of being convenient for rationally arranges dispatch route and dispatch instrument according to the dispatch task distribution quantity and the dispatch task distribution time that predict shift information corresponds, improves dispatch object's work efficiency, reduces dispatch instrument scheduling cost.

It should be understood that the apparatus shown in fig. 8 and its modules may be implemented in various ways. For example, in some embodiments, an apparatus and its modules may be implemented by hardware, software, or a combination of software and hardware. Wherein the hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory for execution by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the methods and systems described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided, for example, on a carrier medium such as a diskette, CD-or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules of the present application may be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, for example, or by a combination of the above hardware circuits and software (e.g., firmware).

It should be noted that the above description of the apparatus and its modules is for convenience only and should not limit the present application to the scope of the illustrated embodiments. It will be appreciated by those skilled in the art that, given the teachings of the present system, any combination of modules or sub-system configurations may be used to connect to other modules without departing from such teachings. For example, the first obtaining module 801, the second obtaining module 802, the predicting module 803, the proportion determining module 804 and the allocating module 805 disclosed in fig. 8 may be different modules in one system, or may be a module that implements the functions of two or more modules, for example, the predicting module 803 and the proportion determining module 804 may be two modules having the functions of predicting and determining proportion respectively, or may be a module having both the functions of predicting and determining proportion.

In order to better implement the assignment task in the embodiment of the present application, on the basis of the assignment task, an embodiment of the present application further provides a system for assigning an assignment task, which integrates any one of the devices for assigning an assignment task provided in the embodiment of the present application, where the system includes:

one or more processors;

a memory; and

one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the processor to perform the steps of the distributed dispatch task method of any of the above distributed dispatch task embodiments.

Fig. 9 is a schematic structural diagram of a task allocation and dispatch system according to an embodiment of the present application, specifically:

the dispatch task system may include a processor 901 of one or more processing cores, memory 902 of one or more computer-readable storage media. Those skilled in the art will appreciate that the configuration shown in FIG. 9 does not constitute a limitation of a system for distributing dispatch tasks and may include more or fewer components than shown, or some components in combination, or a different arrangement of components. Wherein:

the processor 901 is a control center of the system, connects various parts of the entire system using various interfaces and lines, and performs various functions of the system and processes data by running or executing software programs and/or modules stored in the memory 902 and calling data stored in the memory 902, thereby monitoring the system as a whole. Optionally, processor 901 may include one or more processing cores; the Processor 901 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, and preferably the processor 901 may integrate an application processor, which handles primarily the operating system, user interfaces, application programs, etc., and a modem processor, which handles primarily wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 901.

The memory 902 may be used to store software programs and modules, and the processor 901 executes various functional applications and data processing by operating the software programs and modules stored in the memory 902. The memory 902 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created from use of the assignment dispatch task system, and the like. Further, the memory 902 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory 902 may also include a memory controller to provide the processor 901 access to the memory 902.

Although not shown, the assignment task assigning system may further include a display unit and the like, which will not be described herein. Specifically, in this embodiment, the processor 901 in the task allocation and dispatch system loads an executable file corresponding to a process of one or more application programs into the memory 902 according to the following instructions, and the processor 901 runs the application programs stored in the memory 902, so as to implement various functions as follows:

acquiring logistics data associated with a transportation object, wherein the logistics data comprises position information of the transportation object and dispatching task data associated with logistics nodes;

obtaining dispatching data historically distributed by the logistics nodes;

predicting the time when the transportation object reaches the logistics node based on the position information of the transportation object;

determining distribution proportion of dispatching objects based on dispatching data of the historical distribution;

and determining dispatching task distribution time and dispatching task distribution quantity of the dispatching object based on the time of the transportation object reaching the logistics node, the dispatching task data and the distribution proportion.

It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions or by associated hardware controlled by the instructions, which may be stored in a computer readable storage medium and loaded and executed by a processor.

To this end, an embodiment of the present invention provides a computer-readable storage medium, which may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like. Stored thereon, is a computer program that is loaded by a processor to perform the steps of any of the methods of assigning dispatch tasks provided by embodiments of the present invention. For example, the computer program may be loaded by a processor to perform the steps of:

obtaining dispatching data historically distributed by the logistics nodes;

In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and parts that are not described in detail in a certain embodiment may refer to the above detailed descriptions of other embodiments, and are not described herein again.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be considered merely illustrative and not restrictive of the broad application. Various modifications, improvements and adaptations to the present application may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present application and thus fall within the spirit and scope of the exemplary embodiments of the present application.

Also, this application uses specific language to describe embodiments of the application. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the present application is included in at least one embodiment of the present application. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the present application may be combined as appropriate.

Accordingly, various aspects of the present application may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the present application may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media.

The computer storage medium may comprise a propagated data signal with the computer program code embodied therewith, for example, on baseband or as part of a carrier wave. The propagated signal may take any of a variety of forms, including electromagnetic, optical, etc., or any suitable combination. A computer storage medium may be any computer-readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code located on a computer storage medium may be propagated over any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or any combination of the preceding.

Computer program code required for the operation of various portions of the present application may be written in any one or more programming languages, including an object oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C + +, C #, VB.NET, Python, and the like, a conventional programming language such as C, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, a dynamic programming language such as Python, Ruby, and Groovy, or other programming languages, and the like. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any network format, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or in a cloud computing environment, or as a service, such as a software as a service (SaaS).

Additionally, the order in which elements and sequences of the processes described herein are processed, the use of alphanumeric characters, or the use of other designations, is not intended to limit the order of the processes and methods described herein, unless explicitly claimed. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.

Similarly, it should be noted that in the preceding description of embodiments of the application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to require more features than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

The method for distributing and dispatching tasks provided by the embodiment of the application is described in detail, a specific example is applied in the description to explain the principle and the implementation of the invention, and the description of the embodiment is only used for helping to understand the method and the core idea of the invention; meanwhile, for those skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims

1. A method of distributing dispatch tasks, the method comprising:

obtaining dispatching data historically distributed by the logistics nodes;

2. The method of claim 1, wherein the predicting the time at which the transport object arrives at the logistics node based on the location information of the transport object comprises:

3. The method of claim 2, wherein the obtaining the historical average arrival time of the transportation object at the logistics node comprises:

and determining the historical average arrival time of the transportation object to the logistics node based on the historical logistics data.

4. The method of claim 3, wherein the historical logistics data comprises historical departure times, historical departure locations, historical arrival times, and historical arrival locations, and wherein determining the historical average arrival time of the transportation object at the logistics node based on the historical logistics data comprises:

determining correlated historical logistics data based on the historical logistics data, wherein a historical departure place of the correlated historical logistics data is correlated with the position information of the transportation object, and a historical arrival place of the correlated historical logistics data is correlated with the logistics node;

determining a historical average arrival time based on the correlated historical logistics data.

5. The method of claim 1, wherein the historically assigned dispatch data includes shift information, and wherein determining an allocation proportion of dispatch objects based on the historically assigned dispatch data comprises:

6. The method of claim 5, wherein the determining the dispatch task allocation time and the dispatch task allocation quantity for the dispatch object based on the time of arrival of the transport object at the logistics node, the dispatch task data, and the allocation proportion comprises:

acquiring shift data of the logistics nodes;

7. The method of claim 1, wherein the historically allocated dispatch data includes unit area information, and wherein determining an allocation proportion of dispatch objects based on the historically allocated dispatch data comprises:

8. The method of claim 7, wherein the dispatch task data comprises unit area data, and wherein determining the dispatch task allocation time and the dispatch task allocation quantity for the dispatch object based on the time of arrival of the transport object at the logistics node, the dispatch task data, and the allocation ratio comprises:

determining unit dispatch task data based on the unit area data;

9. The method of claim 1, wherein the historically assigned dispatch data includes shift information and unit area information, and wherein determining an allocation proportion of dispatch objects based on the historically assigned dispatch data comprises:

10. The method of claim 9, wherein the dispatch task data comprises unit area data, and wherein determining the dispatch task allocation time and the dispatch task allocation quantity for the dispatch object based on the time of arrival of the transport object at the logistics node, the dispatch task data, and the allocation ratio comprises:

acquiring shift data of the logistics nodes;

determining unit dispatch task data based on the unit area data;

11. The method of claim 1, wherein the determining the dispatch task allocation time and the dispatch task allocation quantity for the dispatch object based on the time of arrival of the transport object at the logistics node, the dispatch task data, and the allocation proportion comprises:

acquiring shift data of the logistics nodes;

12. An apparatus for distributing dispatch tasks, the apparatus comprising:

the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring logistics data associated with a transportation object, and the logistics data comprises position information of the transportation object and dispatching task data associated with a logistics node;

the prediction module is used for predicting the time when the transportation object reaches the logistics node based on the position information of the transportation object;

the second acquisition module is used for acquiring dispatching data historically distributed by the logistics nodes;

the proportion determining module is used for determining the distribution proportion of the dispatching objects based on the dispatching data of the historical distribution; and

and the distribution module is used for determining the distribution time and the distribution quantity of the dispatching tasks of the dispatching objects based on the time of the transportation objects reaching the logistics nodes, the dispatching task data and the distribution proportion.

13. A system for distributing dispatch tasks, the system comprising:

one or more processors;

a memory; and

one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the processor to implement the method of assigning dispatch tasks of any of claims 1-11.

14. A computer-readable storage medium, having stored thereon a computer program which is loaded by a processor for performing the steps in the method of assigning dispatch tasks according to any of claims 1 to 11.