CN112766650A

CN112766650A - Method and device for determining scheduling scheme

Info

Publication number: CN112766650A
Application number: CN202011619674.1A
Authority: CN
Inventors: 吴佳蔓; 吴辰晔; 缪莹莹; 李群; 秦永立; 马楠; 方君; 谢书昭
Original assignee: Beijing Didi Infinity Technology and Development Co Ltd
Current assignee: Beijing Didi Infinity Technology and Development Co Ltd
Priority date: 2020-12-31
Filing date: 2020-12-31
Publication date: 2021-05-07

Abstract

The application provides a method and a device for determining a scheduling scheme, which comprise the following steps: acquiring service attribute information of each travel order in a target order set and current position information of service providers located at different positions in a target area; generating a plurality of scheduling schemes based on the service attribute information of each travel order in the target order set and the current position information of the service providing terminal; for each scheduling scheme, determining the resource consumption of executing the scheduling scheme according to each service scheme in the scheduling scheme; according to the resource consumption, the service schemes used by the multiple travel orders in the target order set are selected from the target scheduling schemes in the multiple scheduling schemes, and according to the determining method and the determining device, the traditional scheme can be optimized towards the global optimal direction, namely the reasonability of allocation of each travel order is considered from the global perspective, and the allocation accuracy is improved.

Description

Method and device for determining scheduling scheme

Technical Field

The present application relates to the field of full scheduling, and in particular, to a method and an apparatus for determining a scheduling scheme.

Background

The key bottleneck for improving the life quality of the metropolis is the problem of lightening the overload of a traffic system. One effective way to relieve traffic system stress is to introduce shared traffic into the system. For example, the vehicle and the travel order providing travel service are matched through the online vehicle sharing platform to realize the full scheduling of the vehicle and the travel order.

At present, an online vehicle sharing platform is dedicated to improving the matching degree of a vehicle and a travel order, but the matching accuracy of the vehicle and the travel order determined by the online vehicle sharing platform is low due to the limitation of a decision process based on time coupling and the absence of the future travel order, so that an accurate full-scheduling scheme of the vehicle and the travel order cannot be provided.

Disclosure of Invention

In view of this, an object of the present application is to provide a method and an apparatus for determining a scheduling scheme, which can solve the problems that in the prior art, the decision process is limited based on time coupling and future travel orders are missed, and the matching accuracy between a vehicle and a travel order determined by an online vehicle sharing platform is low by searching for a global optimal manner, and this manner of determining a scheduling scheme optimizes a conventional scheme in a global optimal direction, that is, the rationality of allocation of each travel order is considered from a global perspective, and the accuracy of allocation is improved.

The application mainly comprises the following aspects:

in a first aspect, an embodiment of the present application provides a method for determining a scheduling scheme, including: acquiring service attribute information of each travel order in a target order set and current position information of service providers located at different positions in a target area; each travel order in the target order set is a travel order which is executed in a target area and is in a to-be-distributed state; the service attribute information comprises service time and service position; generating a plurality of scheduling schemes based on the service attribute information of each travel order in the target order set and the current position information of the service providing terminal; each scheduling scheme comprises a service scheme for each travel order in the target order set; the service scheme comprises a service providing end and a service route matched with the travel order; for each scheduling scheme, determining the resource consumption of executing the scheduling scheme according to each service scheme in the scheduling scheme; and selecting a service scheme used for a plurality of travel orders in the target order set from target scheduling schemes in a plurality of scheduling schemes according to the resource consumption.

In a possible implementation, the determining method further includes:

aiming at a target travel order in a target order set, determining a target service provider capable of bearing the travel order according to the target scheduling scheme;

and aiming at a target travel order in the target order set, distributing the travel order to a target service providing terminal, and sending reminding information indicating that the travel order has been picked up to a service request terminal sending the target travel order.

In a possible implementation manner, the step of generating a plurality of scheduling plans based on the service attribute information of each travel order in the target order set and the current location information of the service provider includes:

generating a plurality of candidate scheduling schemes based on the service attribute information of each travel order in the target order set and the current position information of the service providing terminal;

determining the execution reasonableness of each candidate scheduling scheme according to any one or more of the following information: the taking cost of the first order, the continuous service cost of different orders, the execution cost of each order and the taking probability of a driver for a specified travel order;

and selecting a plurality of scheduling schemes from the plurality of candidate scheduling schemes according to the execution reasonable degree of each candidate scheduling scheme.

In one possible embodiment, the service location comprises a service origin location; the service time includes a service start time;

the step of generating a plurality of candidate scheduling schemes based on the service attribute information of each travel order in the target order set and the current position information of the service provider includes:

for each travel order, respectively calculating the time required by each service provider to reach the travel order service starting point position according to the service starting point position of the travel order, the current position information of the service providers positioned at different positions in the target area and the road communication condition information of different areas in the target area;

for each travel order, determining a service provider capable of bearing the travel order according to the service time of the travel order and the time required for each service provider to reach the travel order service starting point position;

and generating a plurality of candidate scheduling schemes according to the service providing terminal capable of bearing the travel orders.

In one possible embodiment, the service location comprises a service end location and a service start location; the service time includes a service start time and a service end time;

for each travel order, calculating an order connection distance for continuously executing each other travel order after the travel order is finished according to the service end point position of the travel order and the service starting point positions of other travel orders;

selecting a continuous service travel order which can be continuously served after the travel order is finished from other travel orders according to the order connection distance between the travel order and each other travel order, the predicted service end time of the travel order and the service start time of other travel orders;

and generating a plurality of candidate scheduling schemes according to the travel order to be continuously served corresponding to each travel order.

In a possible implementation manner, the step of generating a plurality of candidate scheduling schemes based on the service attribute information of each travel order in the target order set and the current location information of the service provider includes:

for each service provider, determining the probability of the service provider for carrying each travel order according to the historical service preference data of the service provider and the service attribute information of each travel order;

for each service provider, determining a travel order which can be accepted by the service provider according to the probability of accepting each travel order by the service provider;

and generating a plurality of candidate scheduling schemes according to the travel orders which can be accepted by each service provider.

for each travel order, respectively calculating the time required by each service provider to reach the travel order service starting point position according to the service starting point position of the travel order and the current position information of the service providers at different positions in the target area;

for each travel order, determining whether different driver nodes in the network directed graph are connected with order nodes corresponding to the travel orders or not according to a service provider capable of bearing the travel orders;

establishing a network directed graph according to whether a driver node and an order node in the network directed graph are connected; the network directed graph consists of driver nodes and order nodes, and the connected driver nodes and order nodes represent that a driver can take a travel order corresponding to the order nodes;

and generating a plurality of candidate scheduling schemes according to the connection relation between the order nodes and the driver nodes in the established network directed graph.

calculating the order connection distance between the travel order and each other travel order according to the service end point position of the travel order and the service starting point positions of other travel orders aiming at each travel order;

for each travel order, determining whether order nodes of other different travel orders in the network directed graph are connected with order nodes corresponding to the travel orders according to a continuous service travel order capable of being continuously served after the travel order is completed;

establishing a network directed graph according to whether order nodes of different other travel orders in the network directed graph are connected with order nodes corresponding to the travel orders; the network directed graph consists of a driver node and an order node, and the two connected order nodes and the order node represent that a driver can continuously complete a travel order corresponding to another travel node after completing the travel order corresponding to one order node;

and generating a plurality of candidate scheduling schemes according to the connection relation among different order nodes in the established network directed graph.

for each service provider, determining the probability of the service provider for carrying each travel order according to the historical data of the service provider and the service attribute information of each travel order;

for each service provider, determining whether different order nodes in a network directed graph are connected with a driver node corresponding to the service provider according to a travel order which can be accepted by the service provider;

establishing a network directed graph according to whether the order node and the driver node in the network directed graph are connected; the network directed graph consists of order nodes and driver nodes, and the connected order nodes and driver nodes represent that a driver can take a travel order corresponding to the order nodes;

In one possible embodiment, the travel orders in the target order set include: real travel orders and predicted travel orders;

the real travel order is a travel order issued by the service request terminal;

the predicted travel orders are travel orders predicted to appear in the target area according to historical travel order data.

In one possible embodiment, the resource consumption comprises any one or more of the following:

the taking cost of the first order, the continuous service cost of different orders, the execution cost of each order and the taking probability of a driver for a specified travel order;

the carrying cost of the first order is calculated according to a route from the current position of the service provider to the service starting position of the carried first travel order;

the continuous service cost of different orders is calculated according to a route from the service end position of the previous travel order to the service start position of the next travel order;

the execution cost of each order is calculated according to a route from a service starting position to a service end position of the travel order, or is calculated according to the quantity of predicted travel orders which can be continuously served after the real travel order is finished;

and the taking-over probability of the driver for the specified travel order is calculated according to the historical data of the service provider and the service attribute information of the taken-over travel order.

In one possible embodiment, the accommodation cost of the first order comprises any one or more of the following:

the time cost of taking up the first order, the cost of taking up the first order;

the continuous service costs of the different orders include any one or more of:

continuous service time costs for different orders, continuous service cost costs for different orders;

the cost of execution for each order may include any one or more of:

the execution time cost per order, the execution fee cost per order.

In a second aspect, an embodiment of the present application further provides a device for determining a scheduling scheme, including: the acquisition module is used for acquiring the service attribute information of each travel order in the target order set and the current position information of service providers located at different positions in the target area; each travel order in the target order set is a travel order which is executed in a target area and is in a to-be-distributed state; the service attribute information comprises service time and service position;

the generating module is used for generating a plurality of scheduling schemes based on the service attribute information of each travel order in the target order set and the current position information of the service providing terminal; each scheduling scheme comprises a service scheme for each travel order in the target order set; the service scheme comprises a service providing end and a service route matched with the travel order;

a determining module, for each scheduling scheme, determining resource consumption for executing the scheduling scheme according to each service scheme in the scheduling scheme;

and the screening module is used for selecting a service scheme used by a plurality of travel orders in the target order set from target scheduling schemes in a plurality of scheduling schemes according to the resource consumption.

In a possible implementation, the determining means further includes:

the service provider determining module is used for determining a target service provider capable of bearing a travel order according to the target scheduling scheme aiming at the target travel order in the target order set;

and the distribution module is used for distributing the travel order to the target service providing terminal according to the target travel order in the target order set and sending reminding information indicating that the travel order is taken to the service request terminal sending the target travel order.

In one possible implementation, the generating module includes:

the candidate scheduling scheme generating unit is used for generating a plurality of candidate scheduling schemes based on the service attribute information of each travel order in the target order set and the current position information of the service providing terminal;

a determining unit, for determining the execution reasonableness of each candidate scheduling scheme according to any one or more of the following information: the taking cost of the first order, the continuous service cost of different orders, the execution cost of each order and the taking probability of a driver for a specified travel order;

and the screening unit is used for selecting a plurality of scheduling schemes from the plurality of candidate scheduling schemes according to the execution reasonableness of each candidate scheduling scheme.

the candidate scheduling scheme generation unit is to:

In one possible embodiment, the candidate scheduling scheme generating unit is configured to:

the candidate scheduling scheme generation unit is to:

for each travel order, calculating order connection distance between the travel order and each other travel order according to the road communication condition information of the different areas, the service end point position of the travel order and the service starting point positions of other travel orders;

the real travel order is a travel order issued by the service request terminal;

the cost of execution for each order may include any one or more of:

the execution time cost per order, the execution fee cost per order.

According to one aspect of the present application, an electronic device may include a storage medium and a processor in communication with the storage medium. The storage medium stores machine-readable instructions executable by the processor. When the electronic device is operated, the processor is communicated with the storage medium through the bus, and when the processor executes the machine-readable instructions, one or more of the following operations can be executed:

in a third aspect, an embodiment of the present application further provides an electronic device, including: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating via the bus when the electronic device is operating, the machine-readable instructions when executed by the processor performing the steps of a method of determining a scheduling scheme as described above.

In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to perform the steps of the method for determining a scheduling scheme.

In a fifth aspect, the present application further provides a computer program product, which includes a computer program/instruction, and when executed by a processor, the computer program/instruction implements the steps of the method for determining a scheduling scheme as described above.

According to the method for determining the scheduling scheme, a plurality of scheduling schemes can be generated through the acquired service attribute information of each travel order in the target order set, the current position information of the service providing terminal and the road communication condition information of different areas, then the resource consumption of each scheduling scheme is calculated respectively, and the target scheduling scheme used for the travel orders in the target order set is selected from the scheduling schemes according to the resource consumption. The mode of determining the scheduling scheme optimizes the traditional scheme towards the global optimal direction, namely, the rationality of allocation of each travel order is considered from the global perspective, and the allocation accuracy is improved.

In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.

FIG. 1 illustrates a block diagram of a scheduling scheme determination system in accordance with some embodiments of the present application;

fig. 2 is a flowchart illustrating a method for determining a scheduling scheme according to an embodiment of the present application;

FIG. 3 is a flow chart illustrating steps provided by an embodiment of the present application to generate a plurality of candidate scheduling schemes;

fig. 4 illustrates an example of a network directed graph provided by an embodiment of the present application;

fig. 5 is a schematic structural diagram illustrating a determining apparatus of a scheduling scheme provided in an embodiment of the present application;

fig. 6 shows a schematic structural diagram of an electronic device provided in an embodiment of the present application.

Detailed Description

To make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it should be understood that the drawings in the present application are for illustrative and descriptive purposes only and are not used to limit the scope of protection of the present application. Additionally, it should be understood that the schematic drawings are not necessarily drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of the present application. It should be understood that the operations of the flow diagrams may be performed out of order, and that steps without logical context may be performed in reverse order or concurrently. One skilled in the art, under the guidance of this application, may add one or more other operations to, or remove one or more operations from, the flowchart.

In addition, the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.

The following method, apparatus, electronic device or computer-readable storage medium in the embodiments of the present application may be applied to any scenario that requires determination of a scheduling scheme, and the embodiments of the present application do not limit a specific application scenario, and any scheme that uses the method and apparatus for determining a scheduling scheme provided in the embodiments of the present application is within the scope of protection of the present application.

It is noted that, before the present application is proposed, an online vehicle sharing platform (e.g., a server, a cloud service platform, etc.) is working on improving the matching degree of a vehicle and a travel order, but based on the limitation of a time-coupled decision process and the absence of a future order, the matching degree of the vehicle and the travel order determined by the online vehicle sharing platform is low, and therefore, an accurate full-scheduling scheme of the vehicle and the travel order cannot be given.

In view of the above problem, in the embodiment of the present application, by obtaining service attribute information of each travel order in a target order set and current location information of a service provider located at different locations in a target area, a plurality of scheduling schemes are generated based on the service attribute information of each travel order in the target order set and the current location information of the service provider, then, for each scheduling scheme, according to each service scheme in the scheduling scheme, a resource consumption amount for executing the scheduling scheme is determined, and according to the resource consumption amount, a service scheme used for a plurality of travel orders in the target order set is selected from target scheduling schemes in the plurality of scheduling schemes. The mode of determining the scheduling scheme optimizes the traditional scheme towards the global optimal direction, namely, the rationality of allocation of each travel order is considered from the global perspective, and the allocation accuracy is improved.

Fig. 1 is a schematic architecture diagram of a scheduling scheme determining system 100 provided in an embodiment of the present application. For example, the dispatch scenario determination system 100 may be an online transportation service platform for transportation services such as taxi cab, designated drive service, express, carpool, bus service, driver rental, or regular service, or any combination thereof. The scheduling scheme determination system 100 may include one or more of a server 110, a network 120, a service requester 130, a service provider 140, and a database 150.

In some embodiments, the server 110 may include a processor. The processor may process information and/or data related to the service request to perform one or more of the functions described herein. For example, the processor may determine the target vehicle based on a service request obtained from the service requester 130. In some embodiments, a processor may include one or more processing cores (e.g., a single-core processor (S) or a multi-core processor (S)). Merely by way of example, a Processor may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), an Application Specific Instruction Set Processor (ASIP), a Graphics Processing Unit (GPU), a Physical Processing Unit (PPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), a controller, a microcontroller Unit, a Reduced Instruction Set computer (Reduced Instruction Set computer), a microprocessor, or the like, or any combination thereof.

In some embodiments, the device types corresponding to the service request end 130 and the service providing end 140 may be mobile devices, such as smart home devices, wearable devices, smart mobile devices, virtual reality devices, or augmented reality devices, and the like, and may also be tablet computers, laptop computers, or built-in devices in motor vehicles, and the like.

In some embodiments, a database 150 may be connected to the network 120 to communicate with one or more components (e.g., the server 110, the service requester 130, the service provider 140, etc.) in the scheduling scheme determination system 100. Determination of scheduling scheme one or more components in system 100 may access data or instructions stored in database 150 via network 120. In some embodiments, the database 150 may be directly connected to one or more components in the scheduling scheme determination system 100, or the database 150 may be part of the server 110.

The following describes a method for determining a scheduling scheme provided in an embodiment of the present application in detail with reference to the content described in the system 100 for determining a scheduling scheme shown in fig. 1.

Fig. 2 is a schematic flowchart of a method for determining a scheduling scheme according to an embodiment of the present application. It should be noted that the scheduling scheme proposed in the present application may be a scheduling scheme for dual-end service. Here, the dual-end service refers to a service that the server allocates a service order issued by the service request terminal to a specified service provider and the specified service provider provides the service request terminal. For example, the dual-end service applicable to the present application may be a travel service, such as an online taxi-taking service, and is not applicable to a cargo delivery type travel service, such as a take-out delivery service or a courier delivery service.

Specifically, the determining method may be executed by the server 110 in the scheduling scheme determining system 100, and the specific execution process is as follows:

step S201: and acquiring the service attribute information of each travel order in the target order set and the current position information of service providers located at different positions in the target area. Here, each travel order in the target order set is a travel order executed in a target area in a to-be-allocated state; the service attribute information includes a service time and a service location.

It should be noted that the travel order may be a reservation order in a to-be-allocated state executed in the target area and generated in a certain period of time, or the travel order may be a reservation order in a to-be-allocated state executed in the target area and generated in a different period of time.

Further, the travel orders in the target order set may include: the real travel order and the forecast travel order, wherein the real travel order is the travel order which is already issued by the service request terminal. The predicted travel orders are travel orders predicted to appear in the target area according to historical travel order data. Here, the historical travel order data may include travel order execution situations when travel orders generated in a predetermined period of time (e.g., one day, two days, one week, etc.) in the past are executed to different stages. Travel orders that are about to appear in the target area may be predicted from historical travel order data using any means now available. Further, it should be understood that the travel orders in the target order set may also include only real travel orders.

The service attribute information of the travel order may include a service time and a service location of the travel order. The service time of the travel order may include a service start time, which may be the earliest time the passenger desires the service to start, and a service end time, which may be the latest time the passenger can accept the service to end. The service location of the travel order may include a service start location and a service end location.

Taking the travel order as an on-line taxi taking reservation order as an example, the service starting time is reserved boarding time, the service ending time is reserved getting-off time, the service starting point position is a reserved boarding place, and the service ending point position is a reserved getting-off position.

Further, it should be noted that the target area may be a specific area (e.g., a city, an area of a city, etc.). In some embodiments, the target area may be an administrative area. Administrative regions may represent countries, provinces, cities, districts, counties, streets, etc., or any combination thereof. In some embodiments, the target region may be an area manually specified by an on-demand service provider. In some embodiments, the target region may be a geographic area housing a point of interest (POI). In certain embodiments, the POI may be a hospital, school, park, road, bridge, river, lake, train station, airport, company, hotel, attraction, mountain, residential community, or the like, or any combination thereof. In some embodiments, the geographic area has a predetermined range, which may be any reasonable value that contains a POI. In some embodiments, the predetermined range of POIs may be a default setting of the scheduling scheme determination system 100.

Step S202: and generating a plurality of scheduling schemes based on the service attribute information of each travel order in the target order set and the current position information of the service providing terminal.

Here, each scheduling plan includes a service plan for each travel order in the target order set. The service plan may include, but is not limited to, the service provider and the service route matched to the travel order. For example, taking the travel order as the online taxi taking reservation order as an example, the service plan of the online taxi taking reservation order may include a driver (vehicle) taking the online taxi taking reservation order, a driving route, and the like.

Step S203: for each scheduling scheme, a resource consumption amount for executing the scheduling scheme is determined according to each service scheme in the scheduling scheme.

It is noted that, in one example, the resource consumption amount may include any one or more of the following: the taking cost of the first order, the continuous service cost of different orders, the execution cost of each order, and the taking probability of the driver for the specified travel order.

Step S204: and selecting a service scheme used for a plurality of travel orders in the target order set from target scheduling schemes in a plurality of scheduling schemes according to the resource consumption.

The step of generating the plurality of scheduling schemes will be described in detail below in conjunction with fig. 3. Specifically, step S202 may be performed as follows:

step 301: and generating a plurality of candidate scheduling schemes based on the service attribute information of each travel order in the target order set and the current position information of the service providing terminal.

Here, a plurality of candidate scheduling schemes may be generated in various ways based on the service attribute information of each travel order in the target order set and the current location information of the service provider. As will be described in detail below:

in a first example, the service location comprises a service origin location; the service time includes a service start time. In a specific implementation, a plurality of candidate scheduling schemes may be generated according to the following steps:

firstly, for each travel order, respectively calculating the time required by each service provider to reach the travel order service starting point position according to the service starting point position of the travel order and the current position information of the service providers located at different positions in the target area.

In specific implementation, a road traffic map of the target area may be obtained based on road connectivity information of different areas in the target area, and the time required for each service provider to reach the service starting point position of the travel order is calculated for each travel order under the obtained road traffic map.

Taking any one service provider a as an example to explain how to obtain the time required for the service provider a to reach the travel order service starting point position, in a specific implementation, firstly, a route from the current position to the travel order service starting point position of the service provider a may be determined under the obtained road traffic map, and then, the time taken for the service provider a to travel from the current position to the travel order service starting point position at a specific travel speed according to the route may be determined.

Here, the specific travel speed may be determined from historical travel order data of the service provider a, and for example, travel order data of the service provider a for the past ten days may be acquired, an average travel speed of the service provider a for the past ten days may be determined based on the travel order data, and the average travel speed may be taken as the specific travel speed of the service provider a. Here, it is understood that the actual traveling speed may be obtained in other forms based on the historical travel order data of the service provider a, not only by averaging, but also by the present application without any limitation.

Then, for each travel order, determining a service provider capable of receiving the travel order according to the service time of the travel order and the time required for each service provider to reach the travel order service starting point position.

In a specific implementation, the service time of the travel order may include a service start time of the travel order, for each service provider, after acquiring the time required for the service provider to reach the service start position of the travel order, an arrival time (e.g., beijing time, etc.) when the service provider reaches the service start position of the travel order may be obtained, further, it is determined whether the arrival time is before the service start time of the travel order, and if the arrival time is before the service start time of the travel order, a neutral time between the arrival time and the service start time of the travel order is determined, where the neutral time refers to a time taken from the arrival time to reach the service start time of the travel order. The neutral time corresponding to all the service providers can be obtained by the method, the service provider corresponding to the shortest neutral time is selected from the neutral time corresponding to all the service providers, and the service provider is determined to be the service provider capable of receiving the travel order.

And finally, generating a plurality of candidate scheduling schemes according to the service provider capable of bearing the travel orders.

In specific implementation, the service provider of each travel order can be determined, a supporting relationship between the travel order and the service provider is established, and then a plurality of candidate scheduling schemes are obtained.

In a second example, the service location comprises a service end location and a service start location; the service time includes a service start time and a service end time. In a specific implementation, a plurality of candidate scheduling schemes may be generated according to the following steps:

firstly, for each travel order, calculating the order connection distance of each other travel order after the travel order is finished according to the service end point position of the travel order and the service starting point positions of other travel orders.

In specific implementation, the road traffic map of the target area may be obtained based on the road connectivity information of different areas in the target area. And for each travel order, calculating the order connection distance between the travel order and each other travel order according to the road communication condition information of different areas, the service end point position of the travel order and the service starting point positions of other travel orders.

Taking a travel order B and a travel order C as an example, how to obtain the order connection distance between the travel order B and the travel order C is described. In specific implementation, firstly, a route from the service end position of the travel order B to the service start position of the travel order C may be determined under the acquired road traffic map. Then, a route traveled by the service provider from the service end position of travel order B to the service start position of travel order C at the reference speed according to the route is determined. Here, the reference speed may be acquired after the completed historical travel order data executed in the target region is statistically processed.

Then, for each travel order, selecting a continuous service travel order capable of being continuously served after the travel order is finished from other travel orders according to the order connection distance between the travel order and each other travel order, the predicted service end time of the travel order and the service start times of other travel orders.

In specific implementation, firstly, for each travel order, acquiring time spent by the service provider in driving from the service end position of the travel order to the service start position of another travel order at a reference speed, further acquiring arrival time (for example, beijing time and the like) of the service provider in arriving at the service start position of another travel order, further determining whether the arrival time is before the service start time corresponding to another travel order, and if the arrival time is before the service start time of another travel order, determining a neutral time between the arrival time and the service start time of another travel order, wherein the neutral time refers to time spent from the arrival time to the service start time of another travel order. The neutral time corresponding to all other travel orders can be obtained by the method, other travel orders corresponding to the shortest neutral time are selected from the neutral time corresponding to all other travel orders, and the other travel orders are determined to be the continuous service travel orders which can be continuously served after the travel orders are completed.

And finally, generating a plurality of candidate scheduling schemes according to the travel orders which are continuously served and correspond to each travel order.

In a third example, in a specific implementation, a plurality of candidate scheduling schemes may be generated according to the following steps:

then, for each service provider, determining the probability of the service provider for carrying each travel order according to the historical data of the service provider and the service attribute information of each travel order.

It should be noted that, the historical service preference data of the service provider may include, but is not limited to, an accident situation, a historical order taking situation, a service habit situation, an order taking willingness situation, and the like of the service provider, for example, the accident situation may include a historical accident occurrence place of the service provider; the historical order taking situation can comprise the service starting point position, the service end point position, the service starting time, the service ending time and the like of the travel orders taken by the service providing terminal in the past; the service habit conditions can include the resistance of the service provider to the driving distance or driving region; the order taking willingness condition may include an admission degree of the service providing end to an area to which a service starting point position or a service ending point position of the accepted travel order belongs, and the like.

In specific implementation, statistical calculation can be performed on the historical data of the service providing terminal and the service attribute information of each travel order, so as to obtain the probability that the service providing terminal bears each travel order.

Next, for each service provider, determining a travel order that the service provider can take according to the probability that the service provider takes each travel order.

In specific implementation, the travel order with the probability greater than the predetermined probability threshold may be determined as the travel order that the service provider can take over. And determining the travel orders with the probability less than or equal to a preset probability threshold value as the travel orders which cannot be taken by the service provider. Here, the probability threshold may be a preset probability threshold set according to an actual scene.

For example, if the service starting point position of the travel order is located in the accident-prone area, the number of times that the service provider rejects the order of the area is large can be obtained by observing the historical data of the service provider, the probability that the service provider accepts the travel order of which the service starting point position is located in the accident-prone area can be calculated according to the rejection number, and whether the service provider can accept the travel order is determined based on the probability.

For example, the area to which the service starting point position of the travel order a belongs is an accident high-occurrence area, according to the order taking willingness condition of the service provider B, the service provider does not take the travel order of the area, the probability that the service provider B takes over the travel order a is 0, and when the preset probability threshold is 0.3, it is determined that the service provider B cannot take over the travel order.

By the method, the service providing terminals which cannot receive orders based on other reasons can be screened, the processing pressure is reduced for subsequent processing, and the processing efficiency is improved.

And finally, generating a plurality of candidate scheduling schemes according to the travel orders which can be accepted by each service provider.

In the present application, as an alternative example, a plurality of candidate scheduling schemes may be generated by a combination of one or more of the above three examples.

As a preferred example of the present application, the candidate scheduling scheme may also be determined according to a relationship between two nodes in the network directed graph. Specifically, the nodes in the network directed graph include the following nodes: driver node, order node, area, source node, and sink node. Before establishing the network directed graph, whether the nodes can be connected or not needs to be determined, and if the nodes can be connected, the relation between the two nodes can be used for determining the scheduling scheme.

In particular, if the driver node and the order node can be connected, this means that the driver can use the order node as the order that he first takes over, i.e. the order can be allocated to this driver at the time of order allocation; if the order node and the order node can be connected, the driver (any driver) can continue to complete the next order after completing the previous order, and the two orders can be distributed to the same driver at the time of order distribution. The following is a brief description of whether different nodes can be connected, and in particular, can be considered from the following points of view:

the first angle is: in case the service location comprises a service start location and the service time comprises a service start time, a plurality of candidate scheduling schemes may be generated by:

step (a): and respectively calculating the time required by each service provider to reach the travel order service starting point position according to the travel order service starting point position and the current position information of the service providers at different positions in the target area. Specific implementation manners can be found in the above description, and are not described in detail herein.

Step (b): and for each travel order, determining a service provider capable of receiving the travel order according to the service time of the travel order and the time required for each service provider to reach the travel order service starting point position. Specific implementation manners can be found in the above description, and are not described in detail herein.

Step (c): and for each travel order, determining whether different driver nodes in the network directed graph are connected with order nodes corresponding to the travel orders according to a service provider capable of bearing the travel orders.

In specific implementation, the driver node corresponding to the service provider capable of receiving the travel order may be connected to the order node corresponding to the travel order. Here, the order nodes include an order starting node and an order ending node, where the order starting node is connected to the order ending node, and the service provider capable of receiving the travel order is connected to the order starting node corresponding to the travel order.

Step (d): establishing a network directed graph according to whether a driver node and an order node in the network directed graph are connected; the network directed graph is composed of driver nodes and order nodes, and the connected driver nodes and order nodes indicate that a driver can take a travel order corresponding to the order nodes.

A step (e): and generating a plurality of candidate scheduling schemes according to the connection relation between the order nodes and the driver nodes in the established network directed graph.

In practice, if the order node and the driver node are connected, this indicates that the driver can use the order node as the first order to be taken, i.e. the driver can be assigned the order at the time of order assignment.

The second angle is: the service position comprises a service end position and a service starting position; in the case where the service time includes a service start time and a service end time, a plurality of candidate scheduling schemes may be generated by:

and (f) calculating the order connection distance between the travel order and each other travel order according to the service end point position of the travel order and the service starting point positions of other travel orders aiming at each travel order. Specific implementation manners can be found in the above description, and are not described in detail herein.

And (g) selecting a continuous service travel order capable of being continuously served after the travel order is finished from other travel orders according to the order connection distance between the travel order and each other travel order, the predicted service end time of the travel order and the service start time of the other travel orders. Specific implementation manners can be found in the above description, and are not described in detail herein.

And (h) determining whether order nodes of different other travel orders in the network directed graph are connected with the order node corresponding to the travel order according to the travel order which can be continuously served after the travel order is finished.

In a specific implementation, for each travel order, an order node corresponding to a travel order capable of being continuously serviced after the travel order is completed may be connected to an order node corresponding to the travel order, where an order end node corresponding to the travel order is connected to an order start node corresponding to a travel order capable of being continuously serviced.

Step (i), establishing a network directed graph according to whether order nodes of different other travel orders in the network directed graph are connected with order nodes corresponding to the travel orders; the network directed graph is composed of a driver node and an order node, and the two connected order nodes and the order node indicate that the driver can continuously complete a travel order corresponding to another travel node after completing the travel order corresponding to one order node.

And (j) generating a plurality of candidate scheduling schemes according to the connection relation among different order nodes in the established network directed graph.

In the implementation, if the order and the order can be connected, it indicates that after the driver (any driver) completes the previous order, the driver can continue to complete the next order, and the two orders can be distributed to the same driver at the time of order distribution.

Third angle: a plurality of candidate scheduling schemes may be generated by:

and (k) determining the probability of each travel order for each service provider according to the historical data of the service provider and the service attribute information of each travel order. Specific implementation manners can be found in the above description, and are not described in detail herein.

And step (l) for each service provider, determining the travel orders which can be accepted by the service provider according to the probability of accepting each travel order by the service provider. Specific implementation manners can be found in the above description, and are not described in detail herein.

And (m) determining whether different order nodes in the network directed graph are connected with the driver node corresponding to the service providing terminal according to the travel orders which can be accepted by the service providing terminal aiming at each service providing terminal.

Step (n), establishing a network directed graph according to whether the order node and the driver node in the network directed graph are connected; the network directed graph is composed of order nodes and driver nodes, and the connected order nodes and driver nodes represent that a driver can take a travel order corresponding to the order nodes.

And (o) generating a plurality of candidate scheduling schemes according to the connection relation between the order nodes and the driver nodes in the established network directed graph.

In the following, the connection relationship of nodes in the network directed graph will be described in a schematic form. Fig. 4 shows an example of a network directed graph provided by an embodiment of the present application. The network directed graph shown in fig. 4 is constructed based on two service providers and four travel orders. Wherein, the driver node 403 corresponds to a first service provider, the driver node 404 corresponds to a second service provider, the order start node 405 and the order end node 406 correspond to a first trip order, the order start node 407 and the order end node 408 correspond to a second trip order, the order start node 409 and the order end node 410 correspond to a third trip order, the order start node 411 and the order end node 412 correspond to a fourth trip order, the area node 413 corresponds to an area to which the first trip order belongs, the area node 414 corresponds to an area to which the fourth trip order belongs, the area node 415 corresponds to an area to which the third trip order belongs, and the network directed graph further includes a source node 401 and a sink node 402, wherein the source node 401 is used for incoming traffic, and the sink node 402 is used for outgoing traffic.

In fig. 4, the driver node 403 is connected to the order start node 407, which indicates that the first service provider corresponding to the driver node 403 can use the second travel order corresponding to the order start node 407 as the first taken order. The order end node 408 is connected to the order start node 411, and indicates that the first service providing end can continue to complete the fourth travel order corresponding to the order start node 411 after completing the second travel order corresponding to the order end node 407.

The driver node 403 is connected to the order start node 405, and indicates that the first service provider corresponding to the driver node 403 can take the first travel order corresponding to the order start node 405 as the first accepted order. The order end node 406 is connected to the order start node 411, and indicates that the first service providing end can continue to complete the fourth travel order corresponding to the order start node 411 after completing the first travel order corresponding to the order end node 406.

The driver node 404 is connected to the order starting node 409, which indicates that the second service provider corresponding to the driver node 404 can take the third travel order corresponding to the order starting node 409 as the first accepted order. The order end node 409 is connected to the order start node 411, and indicates that the second service provider can continue to complete the fourth travel order corresponding to the order start node 411 after completing the third travel order corresponding to the order end node 404.

The driver node 403 is connected to the area node 413, which indicates that the first service provider corresponding to the driver node 404 can directly drive to the area to which the second travel order belongs without taking a pick-up. Driver node 404 is connected to area node 413 and area node 415, respectively, and indicates that the second service provider corresponding to driver node 404 can directly drive to the area to which the second travel order belongs or the area to which the third travel order belongs without taking orders.

The order end node 408 is connected to the area node 413, and indicates an area to which the second travel order corresponding to the order end node 404 belongs. The order end node 412 is connected to the area node 414, and indicates an area to which the fourth travel order corresponding to the order end node 412 belongs. The order end node 410 is connected to the area node 415, and indicates an area to which the third travel order corresponding to the order end node 410 belongs. The order end node 409 is connected to the area node 414, and indicates an area to which the first travel order corresponding to the order end node 409 belongs.

The source node 401 is connected to the driver node 403 and the driver node 404, respectively, to indicate that traffic flows into the driver node 403 and the driver node 404, and the sink node 402 is connected to the area node 413, the area node 414, and the area node 415, respectively, to indicate that all traffic flowing through the area node 413, the area node 414, and the area node 415 flows out through the sink node 402.

Referring back to fig. 3, step S302: determining the execution reasonableness of each candidate scheduling scheme according to any one or more of the following information: the taking cost of the first order, the continuous service cost of different orders, the execution cost of each order, and the taking probability of the driver for the specified travel order.

It should be noted that the receiving cost of the first order reflects the time or cost taken for the service provider to receive the outgoing order. The accommodation cost of the first order may include any one or more of: the time cost of taking over the first order, the cost of taking over the first order. The carrying cost of the first order is calculated according to the route from the current position of the service provider to the service starting point position of the first travel order carried by the service provider. For example, the time taken by the service provider to take the first travel order, i.e., the lead time cost of the first order, may be calculated based on the route and the reference speed of the service provider from the current location to the service start location of the first travel order it takes. In addition, the cost spent by the service provider for accepting the first travel order, that is, the accepting cost of the first order may also be determined based on the route from the current position to the service starting point position of the first travel order accepted by the service provider and the preset cost per distance unit.

The continuous service cost of the different orders reflects the time or cost spent in completing the previous travel order and the travel order that can continue to be serviced after completing the travel order. The continuous service costs of the different orders include any one or more of: time cost of continuous service for different orders, cost of continuous service charges for different orders. And the continuous service cost of the different orders is calculated according to a route from the service end position of the previous travel order to the service start position of the next travel order. For example, the time taken by the service provider to complete taking the first travel order and the consecutive travel orders, that is, the consecutive service time cost of different orders, may be calculated according to the route from the service end position of the previous travel order to the service start position of the next travel order and the reference speed. In addition, the cost spent by the service providing terminal for accepting the first travel order and the continuous travel orders, namely the continuous service fee cost of different orders, can also be determined based on the route from the service end position of the previous travel order to the service start position of the next travel order and the preset fee of each distance unit.

The execution cost of each order reflects the cost of travel orders being completed, and the execution cost of each order includes any one or more of the following: the execution time cost per order, the execution fee cost per order. The execution cost of each order is calculated according to a route from the service starting position to the service end position of the travel order. For example, the time taken by the service provider from the service start position to the service end position of the travel order, that is, the execution time cost of each order may be calculated from the route from the service start position to the service end position of the travel order and the reference speed. In addition, the cost taken to implement the travel order, that is, the execution cost of each order may also be determined based on a route from the service start position to the service end position according to the travel order and a preset cost per distance unit by the service provider.

Or, the execution cost of each order is calculated according to the number of the predicted travel orders which can be continuously served after the real travel orders are completed. For example, for each real travel order in the target order set, the number of predicted travel orders capable of being continuously served after the real travel order is completed is determined, a number set including the number of predicted travel orders capable of being continuously served corresponding to all the real orders is obtained based on the number of predicted travel orders capable of being continuously served corresponding to each real order, each number is compared with a specific value, and an order cost, that is, an execution cost of each order can be obtained according to a comparison result, where the specific value may be a specific percentile of the number set. For example, there are four real travel orders, six predicted travel orders, where there are four predicted travel orders that can be continuously served after the first travel order is completed, three predicted travel orders that can be continuously served after the second travel order is completed, six predicted travel orders that can be continuously served after the third travel order is completed, and five predicted travel orders that can be continuously served after the fourth travel order is completed, the obtained number set is [ 4365 ], if the specific percentile of the number set is 4, the order cost of the travel orders corresponding to the number smaller than 4 is determined as the predetermined value W, and the order cost of the travel orders corresponding to the number greater than or equal to 4 is determined as the value of the number.

The take-over probability of the driver for the specified travel order reflects the probability that the service providing end takes over the travel order. And the taking-over probability of the driver for the specified travel order is calculated according to the historical data of the service provider and the service attribute information of the taken-over travel order. Here, the determination manner of the driver's accommodation probability for the designated travel order is described in detail above, and the detailed description of the present application will be omitted here.

In specific implementation, whether each candidate scheduling scheme can be implemented or not can be comprehensively judged according to the information, for example, when the probability of taking over the specified travel order by the driver is low, the implementation possibility of the candidate scheduling scheme is low, which is equivalent to that the candidate scheduling scheme cannot be implemented.

Step S303: and selecting a plurality of scheduling schemes from the plurality of candidate scheduling schemes according to the execution reasonable degree of each candidate scheduling scheme.

In specific implementation, the candidate scheduling schemes with the execution reasonable degree smaller than the preset threshold value in the candidate scheduling schemes can be removed, so that the scheduling schemes are obtained after screening. The predetermined threshold may be set based on the actual scene.

On the other hand, step S203 may be performed as follows:

in one example, for each scheduling scheme, a standard fee flow algorithm may be used to determine the amount of resource consumption to execute the scheduling scheme from each service scheme in the scheduling scheme.

It should be noted that the edge connecting two nodes in the network directed graph has a weight, and the weight of the edge represents the cost spent on completing two nodes, for example, the weight of the edge between the driver node and the order start node corresponding to the first order to be taken can be represented by the taking cost of the first order. The weight of an edge between an order end node of one order and an order start node of another order may be characterized by the continuous cost of service of the different orders. The weight of an edge between an order start node of an order and an order end node of the order may be characterized by the execution cost of each order. The weight of the edge between the driver node and the node corresponding to the area to which the first taken order or the order of continuous service belongs can be characterized by the take-over probability of the driver for the specified travel order. The weight of the edge between the source node and the driver node and the weight of the edge between the sink node and the regional node are preset weights.

For example, in the example of fig. 4, in a specific implementation, the resource consumption (i.e., at least one of the first order take-over cost, the continuous service cost of different orders, the execution cost of each order, and the take-over probability of the driver for a specific travel order) may be converted through a preset rule to obtain a value conforming to a standard fare flow algorithm, and the obtained data is assigned to a weight of a corresponding edge, and a network directed graph is determined by using the standard fare flow algorithm to calculate the fare flow of different scheduling schemes.

Step S204 may be performed as follows:

in the above example, in the example of fig. 4, after the cost flows of different scheduling schemes are obtained, an integer optimal solution corresponding to the largest cost flow in the cost flows may be selected. And determining the scheduling scheme under the acquired optimal solution as a target scheduling scheme, and selecting a service scheme used for a plurality of travel orders in the target order set from the target scheduling schemes in the plurality of scheduling schemes.

Further, after selecting the target scheduling scheme, in a preferred example of the present application, the method for determining the scheduling scheme may include the following steps:

step (A): and acquiring the service attribute information of each travel order in the target order set and the current position information of service providers located at different positions in the target area.

Step (B): and generating a plurality of scheduling schemes based on the service attribute information of each travel order in the target order set and the current position information of the service providing terminal.

Step (C): for each scheduling scheme, a resource consumption amount for executing the scheduling scheme is determined according to each service scheme in the scheduling scheme.

Step (D): and selecting a service scheme used for a plurality of travel orders in the target order set from target scheduling schemes in a plurality of scheduling schemes according to the resource consumption.

A step (E): and aiming at a target travel order in the target order set, determining a target service provider capable of bearing the travel order according to the target scheduling scheme.

Step (F): and aiming at a target travel order in the target order set, distributing the travel order to a target service providing terminal, and sending reminding information indicating that the travel order has been picked up to a service request terminal sending the target travel order.

In implementation, first, the travel order may be allocated to the target service provider for the target travel order in the target order set. Then, for a target travel order in the target order set, in response to feedback information sent by the target service provider and indicating that the travel order can be accepted, sending a reminding message that the travel order has been accepted to the service request end sending the travel order, and distributing the target travel order to the target service provider.

Based on the same application concept, a device for determining a scheduling scheme corresponding to the method for determining a scheduling scheme provided in the foregoing embodiment is also provided in the embodiment of the present application, and since the principle of solving the problem of the device in the embodiment of the present application is similar to the method for determining a scheduling scheme in the foregoing embodiment of the present application, the implementation of the device may refer to the implementation of the method, and repeated details are not described again.

Fig. 5 is a schematic structural diagram illustrating a determining apparatus of a scheduling scheme according to an embodiment of the present application.

As shown in fig. 5, the determining means 500 includes:

an obtaining module 501, configured to obtain service attribute information of each travel order in a target order set and current location information of service providers located at different locations in a target area; each travel order in the target order set is a travel order which is executed in a target area and is in a to-be-distributed state; the service attribute information comprises service time and service position;

a generating module 502, configured to generate a plurality of scheduling schemes based on the service attribute information of each travel order in the target order set and the current location information of the service provider; each scheduling scheme comprises a service scheme for each travel order in the target order set; the service scheme comprises a service providing end and a service route matched with the travel order;

a determining module 503, configured to determine, for each scheduling scheme, a resource consumption amount for executing the scheduling scheme according to each service scheme in the scheduling scheme;

the screening module 504 selects a service plan used for a plurality of travel orders in the target order set from target scheduling plans in the plurality of scheduling plans according to the resource consumption.

In a possible implementation, the determining apparatus 500 further includes:

In one possible implementation, the generating module 502 includes:

the candidate scheduling scheme generation unit is to:

the real travel order is a travel order issued by the service request terminal;

the cost of execution for each order may include any one or more of:

the execution time cost per order, the execution fee cost per order.

Referring to fig. 6, fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in fig. 6, the electronic device 600 includes a processor 610, a memory 620, and a bus 630.

The memory 620 stores machine-readable instructions executable by the processor 610, when the electronic device 600 runs, the processor 610 communicates with the memory 620 through the bus 630, and when the machine-readable instructions are executed by the processor 610, the steps of the method for determining the scheduling scheme in the method embodiment shown in fig. 2 may be performed.

An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the step of determining the scheduling scheme in the method embodiments shown in fig. 1 and fig. 2 may be executed.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the exemplary embodiments of the present application, and are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method for determining a scheduling scheme, comprising:

acquiring service attribute information of each travel order in a target order set and current position information of service providers located at different positions in a target area; each travel order in the target order set is a travel order which is executed in a target area and is in a to-be-distributed state; the service attribute information comprises service time and service position;

generating a plurality of scheduling schemes based on the service attribute information of each travel order in the target order set and the current position information of the service providing terminal; each scheduling scheme comprises a service scheme for each travel order in the target order set; the service scheme comprises a service providing end and a service route matched with the travel order;

for each scheduling scheme, determining the resource consumption of executing the scheduling scheme according to each service scheme in the scheduling scheme;

and selecting a service scheme used for a plurality of travel orders in the target order set from target scheduling schemes in a plurality of scheduling schemes according to the resource consumption.

2. The determination method of claim 1, further comprising:

3. The method according to claim 1, wherein the step of generating a plurality of scheduling plans based on the service attribute information of each travel order in the target order set and the current location information of the service provider includes:

4. The determination method of claim 3, wherein the service location comprises a service origin location; the service time includes a service start time;

5. The determination method of claim 3, wherein the service location comprises a service end location and a service start location; the service time includes a service start time and a service end time;

6. The method according to claim 3, wherein the step of generating a plurality of candidate scheduling plans based on the service attribute information of each travel order in the target order set and the current location information of the service provider includes:

7. The determination method of claim 3, wherein the service location comprises a service origin location; the service time includes a service start time;

8. The determination method of claim 3, wherein the service location comprises a service end location and a service start location; the service time includes a service start time and a service end time;

9. The method according to claim 3, wherein the step of generating a plurality of candidate scheduling plans based on the service attribute information of each travel order in the target order set and the current location information of the service provider includes:

10. The method of determining of claim 1, wherein a travel order in the set of target orders comprises: real travel orders and predicted travel orders;

the real travel order is a travel order issued by the service request terminal;

11. The determination method according to claim 1 or 10, wherein the resource consumption amount comprises any one or more of:

12. The determination method of claim 11,

the accommodation cost of the first order comprises any one or more of the following:

the cost of execution for each order may include any one or more of:

the execution time cost per order, the execution fee cost per order.

13. An apparatus for determining a scheduling scheme, comprising:

the acquisition module is used for acquiring the service attribute information of each travel order in the target order set and the current position information of service providers located at different positions in the target area; each travel order in the target order set is a travel order which is executed in a target area and is in a to-be-distributed state; the service attribute information comprises service time and service position;

14. An electronic device, comprising: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating over the bus when the electronic device is operating, the processor executing the machine-readable instructions to perform the steps of the method of any one of claims 1 to 12.

15. A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, is adapted to carry out the steps of the method according to any one of claims 1 to 12.

16. A computer program product comprising a computer program or instructions for implementing the steps of the method of any one of claims 1 to 12 when executed by a processor.