Static dispatching method, device, equipment and medium for inter-city multiple round trip vehicles integrating private car service and carpooling service

Abstract

The present invention provides a static scheduling method, device, equipment and medium for inter-city multiple round-trip vehicles integrating private car service and carpooling service, and relates to the technical field of inter-city static carpooling scheduling. The method comprises: S1, obtaining passengers' scheduled travel data and vehicle set. S2, based on the scheduled travel data and vehicle set, constructing a static scheduling model with maximizing the profit of ordinary carpooling and maximizing the profit of private car service as the optimization goal. S3, according to the static scheduling model, using a sequential line construction algorithm to generate an initial feasible solution. S4, according to the static scheduling model, setting a neighborhood operator based on a one-way trip to perform disturbance. S5, according to the static scheduling model, setting a local search operator based on private car service passengers to improve disturbance. S6, using a variable neighborhood search algorithm to solve according to the static scheduling model, the initial feasible solution, the neighborhood operator and the local search operator to obtain the optimal solution. Among them, the optimal solution is a static scheduling plan.

Description

Technical Field

[0001] The present invention relates to the technical field of inter-city static carpooling scheduling, and in particular to a static scheduling method, device, equipment and medium for inter-city multi-trip round-trip vehicles integrating a private car service and a carpooling service. Background Art

[0002] As people's demand for transportation modes develops in a diversified way, the demand for inter-city travel is growing, and higher requirements are placed on the quality and efficiency of travel. However, in actual operation, the overall utilization rate of inter-city online carpooling services during idle time is often low. In order to solve a series of problems in carpooling services, such as determining the range of passengers getting on and off, reasonably setting service prices, and vehicle route planning, effective measures need to be taken.

[0003] In terms of multi-trip route planning and vehicle private car service time scheduling, existing route planning models have not been able to simultaneously consider the operation of vehicles on multi-trip routes and the scheduling of private car services during specific time periods. These models have difficulty balancing the profits of vehicles performing inter-city carpooling tasks with the profits of performing private car services during idle time periods.

[0004] The purpose of the present invention is to optimize multiple round-trip routes while taking into account the scheduling of special car service time periods, so as to improve the vehicle service quality and company revenue and give full play to the advantages of inter-city carpooling.

[0005] The existing technologies mainly use modern heuristic algorithms such as improved genetic algorithms, dispatching algorithms, particle swarms, etc. to solve the problem of two-sided multi-trip intercity carpooling with private car service. Although these algorithms search for the optimal solution by continuously iteratively updating the initial solution, their convergence speed becomes too slow when the data set is slightly larger, and sometimes they cannot even find a feasible solution.

[0006] Different from the single-trip or multi-trip round-trip route planning problem, the inter-city carpooling travel mode studied in the present invention not only crosses different regions, but also needs to consider the situation where only the private car service is provided within a single time period. That is, a car can complete multiple one-way trips, but only provides private car service within a time period. This is a solution that has not been involved in the prior art, and the present invention provides a new solution in this field.

[0007] In view of this, the applicant hereby files this application after in-depth study of the prior art. Summary of the invention

[0008] The present invention provides a static scheduling method, device, equipment and medium for inter-city multi-trip round-trip vehicles integrating private car service and carpooling service, so as to improve at least one of the above-mentioned technical problems.

[0009] In a first aspect, the present invention provides a static scheduling method for multiple inter-city round-trip vehicles integrating a private car service and a carpooling service, which comprises steps S1 to S6.

[0010] S1. Obtain the passenger's scheduled travel data and vehicle set, wherein the scheduled travel data includes first scheduled travel data for a private car service and second scheduled travel data for an intercity carpooling service.

[0011] S2. Based on the reservation travel data and the vehicle set, a static scheduling model for inter-city multiple round-trip vehicles integrating private car service and carpooling service is constructed with the optimization goal of maximizing the profit of ordinary carpooling and maximizing the profit of private car service.

[0012] S3. Based on the static dispatch model of inter-city multiple round-trip vehicles integrating the private car service and the carpooling service, an initial feasible solution is generated by using a sequential route construction algorithm, wherein the initial feasible solution represents the maximum private car service time in the current one-way trip of the vehicle.

[0013] S4. According to the static scheduling model of the inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, a neighborhood operator based on a one-way trip is set to perturb the feasible solution of the current iteration.

[0014] S5. According to the static scheduling model of inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, a local search operator based on the private car service passengers is set to improve the feasible solution after the disturbance.

[0015] S6. Based on the static scheduling model of inter-city multiple round-trip vehicles integrating the private car service and the carpooling service, the initial feasible solution, the neighborhood operator and the local search operator, a variable neighborhood search algorithm is used to solve and obtain an optimal solution. The optimal solution is a static scheduling plan.

[0016] In a second aspect, the present invention provides a static scheduling device for inter-city multiple round-trip vehicles that integrates private car service and carpooling service, which includes a data acquisition module, a model building module, an initial solution module, a neighborhood operator module, a local search operator module and a solution module.

[0017] The data acquisition module is used to acquire the passenger's scheduled travel data and vehicle set, wherein the scheduled travel data includes the first scheduled travel data of the private car service and the second scheduled travel data of the intercity carpooling service.

[0018] The model building module is used to build a static scheduling model for inter-city multi-trip round-trip vehicles integrating private car service and carpooling service based on the reservation travel data and the vehicle set, with maximizing the profit of ordinary carpooling and maximizing the profit of private car service as the optimization goal.

[0019] The initial solution module is used to generate an initial feasible solution using a sequential route construction algorithm based on the static scheduling model of the inter-city multi-trip vehicles integrating the private car service and the carpooling service. The initial feasible solution represents the maximum private car service time in the current one-way trip of the vehicle.

[0020] The neighborhood operator module is used to set a neighborhood operator based on a one-way trip according to the static scheduling model of the inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, so as to perturb the feasible solution of the current iteration.

[0021] The local search operator module is used to set a local search operator based on the passengers of the private car service according to the static scheduling model of the inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, so as to improve the feasible solution after the disturbance.

[0022] The solution module is used to solve the static scheduling model of the inter-city multiple round-trip vehicles integrating the private car service and the carpooling service, the initial feasible solution, the neighborhood operator and the local search operator using a variable neighborhood search algorithm to obtain an optimal solution. The optimal solution is a static scheduling plan.

[0023] In a third aspect, the present invention provides a static scheduling device for inter-city multiple round trip vehicles integrating a private car service and a carpooling service, comprising a processor, a memory, and a computer program stored in the memory. The computer program can be executed by the processor to implement a static scheduling method for inter-city multiple round trip vehicles integrating a private car service and a carpooling service as described in any paragraph of the first aspect.

[0024] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute a static scheduling method for multiple inter-city round-trip vehicles that integrates private car service and carpooling service as described in any paragraph of the first aspect.

[0025] By adopting the above technical solution, the present invention can achieve the following technical effects:

[0026] The static scheduling method of inter-city multiple round trip vehicles integrating private car service and carpooling service of the present invention aims to maximize the profit of carpooling platform in the scenario of two-way round trip constraint, and considers the problem of two-way carpooling problem and the problem of comprehensive planning of the profit of private car service performed by vehicles in idle time. The sequential construction method is used to generate one-way trips and carpooling routes on the initial feasible solution. According to the characteristics of the problem model, three mixed perturbation operators (i.e., neighborhood operators) for one-way trips are designed to perturb the current solution and four local search operators for private car service are designed to optimize the path and time of private car service, which effectively improves the convergence speed of complex problem models. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 The present invention is a flowchart of a static scheduling method for inter-city multi-trip round-trip vehicles integrating a private car service and a carpooling service.

[0028] Figure 2 A schematic diagram of multiple round trips for vehicles integrating private car services.

[0029] Figure 3 A schematic diagram of a one-way travel connection.

[0030] Figure 4 is the mixed perturbation operator Schematic diagram of .

[0031] Figure 5 is the mixed perturbation operator Schematic diagram of .

[0032] Figure 6 is the mixed perturbation operator Schematic diagram of .

[0033] Figure 7 is the local search operator Schematic diagram of .

[0034] Figure 8 is the local search operator Schematic diagram of .

[0035] Fig. 9 is the local search operator Schematic diagram of .

[0036] Fig.10 is the local search operator Schematic diagram of . DETAILED DESCRIPTION

[0037] Example 1, please refer to Figures 1 to 10 The embodiment of the present invention provides a static scheduling method for inter-city multiple round trip vehicles integrating private car service and carpooling service. The method can be performed by a static scheduling device for inter-city multiple round trip vehicles integrating private car service and carpooling service (hereinafter referred to as static scheduling device), and in particular, by one or more processors in the static scheduling device to implement steps S1 to S5.

[0038] S1, obtaining the passenger's scheduled travel data and vehicle set, wherein the scheduled travel data includes first scheduled travel data of a private car service and second scheduled travel data of an intercity carpooling service.

[0039] The scheduled travel data is the scheduled travel information provided by the passenger to the carpooling platform in advance. The scheduled travel information includes the passenger's designated boarding point and alighting point, and the agreed time for the passenger to board the vehicle. In this embodiment, the scheduled travel information is submitted to the carpooling platform at least one day before departure. In other embodiments, it can be set to be provided to the carpooling platform at least one day in advance.

[0040] set up represents the set of reservation travel orders for cities A and B. is the set of travel reservation orders in city A. is the serial number of the travel reservation order for city A. is the total number of travel reservation orders in city A, is the set of travel reservation orders for city B. is the serial number of the travel reservation order for city B. is the total number of travel reservation orders in city B.

[0041] set up For the Multiple round trips of vehicles to gather at the boarding and alighting points, For the Vehicle No. The pick-up and drop-off points for the outbound trip from city A to city B are gathered. The numbered set of boarding points for passengers in city A. For city A A pick-up point. The numbered set of passengers' drop-off points in city B, For city B A drop-off point. For the Vehicle No. The pick-up and drop-off points for the return trip from city B to city A are gathered. The numbered set of boarding points for passengers in city B, For city B A pick-up point. The numbered set of passengers' drop-off points in city A, For city A A drop-off point.

[0042] The first scheduled travel data of the private car service is the private car service provided by some vehicles during the private car service period. A vehicle has at most a single and continuous private car service period. The number of passengers carried by the vehicle during the private car service period is not greater than the first preset value. The first preset value is half of the maximum passenger capacity of the vehicle, rounded down.

[0043] Among them, a car can have multiple single trips, but there is only one time period for private car service. The private car service time period is the time period when the demand for rides is low. The private car service time periods of different vehicles may be different, and may overlap partially or completely.

[0044] In this embodiment, the maximum passenger capacity of each vehicle is 6 people. Therefore, the vehicle is in its single and continuous private car service period. In other embodiments, the first preset value can be set to other numbers, such as 1 or 2 people, which is not specifically limited in the present invention. For itinerary The start time of the private car service period, For itinerary The end time of the private car service period. For private car service orders in city A, For a private car service order in city B.

[0045] The vehicle is configured to be able to carry multiple trips. The multiple trips include at least two single trips in opposite directions. The single trip refers to a one-way passenger trip from city A to city B, or a one-way passenger trip from city B to city A. Each multiple trip can also only be served by one vehicle, that is, one vehicle corresponds to multiple single trips, and each single trip can only be served by one vehicle.

[0046] set up is the set of all itineraries between cities A and B, is the set of trips from city A to departure. is the trip number from city A to the departure point, Represents the total number of trips from city A to city B, For the itinerary set starting from city B, is the trip number from city B, Represents the total number of trips from city B to city A.

[0047] set up is a set of vehicles departing from cities A and B. Gather vehicles from city A. is the serial number of the vehicle departing from city A, represents the total number of vehicles departing from city A, Gather vehicles from city B. is the serial number of the vehicle departing from city B, Represents the number of vehicles in city B.

[0048] S2, based on the reservation travel data and the vehicle set, with maximizing the profit of ordinary carpooling and maximizing the profit of private car service as the optimization goal, construct a static scheduling model for inter-city multi-trip round-trip vehicles integrating private car service and carpooling service.

[0049] In this embodiment, according to the scheduled travel data and the vehicle set, a static scheduling of multiple round trips of inter-city carpooling integrated with the private car service is performed (eg Figure 2 As shown in the figure, with maximizing the profit of ordinary carpooling and maximizing the profit of private car service as the optimization goals, the objective function of the static scheduling model for inter-city multi-trip round-trip vehicles integrating private car service and carpooling service is as follows.

[0050]

[0051] Objective function 1 represents maximizing revenue, which is the total fare of completed ordinary carpooling services and private car services minus the vehicle path cost.

[0052] in, The serial number of the travel reservation order for city A. The serial number of the travel reservation order for city B. is the set of reservation travel orders for cities A and B, is the line number, For all trips between cities A and B, is the ordinary carpooling fare (yuan), is the first decision variable, Description Order Already Vehicle service for each trip, is the second decision variable, Description Order Already Vehicle service for each trip, For the itinerary collection from city A to departure, is the vehicle serial number, is a set of vehicles departing from cities A and B, The carpooling fare for the private car service (yuan), For itinerary The number of vehicles used for private car services, For itinerary The end time of the private car service period, For itinerary The start time of the private car service period, For trips departing from city B, For itinerary The number of vehicles used for private car services, For itinerary The end time of the private car service period, For itinerary The start time of the private car service period, For the Vehicle No. The pick-up and drop-off points for the outbound trip from city A to city B, and The serial numbers of the boarding and alighting points. express Point and The distance between points, and represents the passenger mileage cost (yuan / km), is the third decision variable, Explain the itinerary Vehicles from Click to Point passing, is the fourth decision variable, Explain the itinerary Vehicles from Click to Point passed.

[0053] The constraints for static scheduling of inter-city multi-trip round-trip vehicles integrating private car service and carpooling service are as follows.

[0054]

[0055] Constraint 2 indicates that any vehicle in the departure trip shall carry no more than X passengers and at least 1 passenger. In this embodiment, X is the number of passengers carried by the vehicle minus 1. In other embodiments, X may be set to other values, which are not specifically limited in the present invention.

[0056]

[0057] Constraint 3 means that the departure passengers' boarding time sequence must be arranged by time.

[0058]

[0059] Constraint 4 is the time constraint that the departing passengers can tolerate the vehicle arriving early or late.

[0060]

[0061] Constraint 5 is the departure channel problem constraint: while adjacent passengers in a passenger chain meet the carpooling condition, they must also meet the vehicle travel time constraint from picking up the first passenger to the departure point.

[0062]

[0063] Constraint 6 is the departure detour coefficient constraint: the total driving distance of the vehicle in the city divided by the distance from the first passenger to the departure point.

[0064]

[0065] Constraint 7 indicates that the departure time of the vehicle at any point is guaranteed to be greater than or equal to the arrival time at that point.

[0066]

[0067] Constraint 8 indicates that the departure ensures that the online ride-hailing service is provided in the order of the vehicle path of the trip. That is, the pick-up point is visited first and then the drop-off point. The pick-up point is before the entrance and exit point of the starting city, and the drop-off point is after the entrance and exit point of the destination city.

[0068]

[0069] Constraints 9 and 10 are used to ensure that the number of round trips on both sides of the vehicle cannot exceed the maximum number of round trips on both sides.

[0070]

[0071] Constraints 11 and 12 are used to ensure that the vehicle must rest for a certain period of time after completing a trip before the next trip is available in the two-sided problem.

[0072]

[0073] Constraint 13 is used to ensure that when the vehicle's two-way round trip number reaches the maximum, the next trip cannot be arranged.

[0074]

[0075] Constraint 14 indicates that the time when the vehicle performs the private car service is within the operating period, and the period is single and continuous.

[0076]

[0077] Constraint 15 means that the vehicle is allowed to have no dedicated car service period, but must complete all inter-city tasks every day.

[0078]

[0079] Constraint 16 indicates that a vehicle can only perform a private car service once at most when traveling multiple times between cities in one day.

[0080]

[0081] Constraint 17 indicates that the number of passengers in the private car service of any vehicle departing from city A shall not exceed 3 and shall be at least 2.

[0082]

[0083] Constraint 18 indicates that a car can have multiple one-way trips but has only one time slot for private car service.

[0084]

[0085] Constraint 19 is that the times for providing the private car service in the two cities can be different.

[0086]

[0087] Constraint 20 indicates that the private car service is based on the passenger's reserved boarding time.

[0088] in, is the set of travel reservation orders for city A, is a set of positive integers, is the set of travel reservation orders for city B, Indicates Vehicles of trips arrived The moment of It means the difference between two elements. Indicates Vehicles of trips arrived The moment of is the increment of the serial number of the boarding and alighting point, Gathering for pick-up and drop-off points, is the trip number from city A to the departure point, Indicates Vehicles of trips arrived The moment of Indicates Vehicles of trips arrived The moment of is the trip number from city B, Indicates order The scheduled boarding time, For orders Maximum Tolerance Vehicle How long you arrive in advance? For orders Maximum Tolerance Vehicle The length of the delay, Indicates order The scheduled boarding time, For orders Maximum Tolerance Vehicle How long you arrive in advance? For orders Maximum Tolerance Vehicle The length of the delay, Assemble the intercity entry and exit points, It is the intercity entrance and exit point of city A. It is the intercity entrance and exit point of city B. Indicates The time when the vehicles of the trip arrive at the intercity entrance and exit point of city A, For the The time when the vehicles of the trip arrive at the intercity entrance and exit point of city B, For the The moment the journey ends, represents the maximum travel time constraint, Indicates The time when the vehicles of the trip arrive at the intercity entrance and exit point of city A, For the The time when the vehicles of the trip arrive at the intercity entrance and exit point of city B, For the The moment the journey ends, represents the detour constraint, For itinerary The distance of For itinerary The distance of For itinerary The distance of From the starting yard to the node The distance of For Node Distance to the final stop, Show itinerary Vehicle leaving The moment of Show itinerary Vehicle leaving The moment of Gather vehicles from city A, The serial number of the vehicle departing from city A, Indicates Number of vehicles traveling back and forth on both sides, Indicates Maximum number of two-way round trips per vehicle, Gather vehicles from city B, The serial number of the vehicle departing from city B, Indicates Number of vehicles traveling back and forth on both sides, Indicates Maximum number of two-way round trips per vehicle, For the The start time of the trip, For the The end time of the trip, For the The start time of the trip, For the The end time of the trip, Indicates vehicle Rest time, is the fifth decision variable, No vehicle is arranged No. Itinerary is the sixth decision variable, No vehicle is arranged No. Itinerary, For vehicles The end time of the operating period, For vehicles The start time of the operating period, The serial number of the travel reservation order. The number of vehicles selected to provide chauffeur-driven services for vehicles on the trip, is the number of round trips, is the seventh decision variable, Private car service orders By itinerary Vehicle services, For private car service orders in City A, For a private car service order in city B.

[0089] S3, using the static dispatch model of the inter-city multiple round trip vehicles integrating the private car service and the carpooling service, and using the sequential route construction algorithm to generate an initial feasible solution, wherein the initial feasible solution represents the maximum private car service time in the current one-way trip of the vehicle.

[0090] In this embodiment, a sequential route construction algorithm is used to generate an initial feasible solution. A one-way trip needs to be constructed first, and then an initial feasible solution is generated based on the one-way trip.

[0091] Constructing a one-way trip includes steps A1 to A6;

[0092] Step A1: Traverse the passenger's reservation data and process each passenger one by one.

[0093] Step A2: Update the passenger's starting point arrival time, determine the time window constraint, and continue to execute if the passenger's starting point arrival time meets the maximum tolerable time window condition.

[0094] Step A3: Update the time when the passenger starts service at the starting point and adjust the schedule.

[0095] Step A4: Determine whether the number of passengers in the current trip is less than the given passenger capacity.

[0096] Step A5: If not, use a greedy strategy based on maximizing revenue to transport passengers in the current trip to their destinations and generate a one-way trip node vector. If yes, continue to process the next trip.

[0097] Step A6: Return to the one-way travel solution.

[0098] Generating an initial feasible solution based on a one-way trip includes steps B1 to B6.

[0099] Step B1: Calculate the one-way itinerary of City A and City B according to the steps of constructing a one-way itinerary.

[0100] Step B2: Select the best one-way trip from the one-way trips of City A and City B as part of the current route, wherein the best one-way trip refers to the shortest distance or the shortest time.

[0101] Step B3: Obtain the number of passengers on the route and determine whether the number of passengers is less than or equal to 3; if the number of passengers is less than or equal to 3, plan the trip as a special car service route, otherwise it is a general service route.

[0102] Step B4: remove the current trip node from the passenger set to prevent duplicate processing.

[0103] Step B5: Update the vehicle route status according to the current trip node information.

[0104] Step B6: Return to vehicle route node

[0105] Specifically, the maximum private car service time in the current one-way trip of the vehicle can be obtained by generating an initial feasible solution of the vehicle route.

[0106] S4, according to the static scheduling model of the inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, a neighborhood operator based on a one-way trip is set to perturb the feasible solution of the current iteration.

[0107] In this embodiment, according to the structural characteristics of the feasible solution in the two-sided multi-trip intercity carpooling route optimization problem integrating the private car service, three neighborhood operators based on one-way travel (the first hybrid perturbation operator, the second hybrid perturbation operator and the third hybrid perturbation operator) are designed to perturb the feasible solution of the current iteration.

[0108] The perturbation operator is used to perturb the travel connection, such as Figure 3As shown, the trip connection point refers to the place where the vehicle starting point is connected to the starting point of the first passenger in a single trip in any route of a feasible solution, or the place where the destination of the last passenger getting off in a trip is connected to the starting point of the first passenger in the next single trip.

[0109] make Indicates The specific designs of these three neighborhood operators are introduced as follows.

[0110] The first mixed perturbation operator Includes steps C1 to C3.

[0111] Step C1: Gather at the vehicle Randomly select two vehicles that have no or only one vehicle with a private car service and , where vehicles The path of is a non-empty feasible solution and First, select the vehicle All one-way trips and vehicles included All one-way travel connections.

[0112] Step C2: Check the vehicle All possible connections and put the vehicle All one-way trips on the route are inserted into the vehicle as a whole At each connection, select the vehicles that meet the constraints 2 to 20. New line.

[0113] Step C3: If the vehicle All connections in the vehicle do not meet If the insertion condition of Return vehicle set In the process, a vehicle is randomly selected again and steps C1 to C2 are repeated until a new route is successfully generated or all possible vehicle combinations fail within the preset number of times. If the operation is successful, the routes of the corresponding two vehicles are updated and the vehicle is deleted. , and then put the new line back into the vehicle set;

[0114] In this embodiment, the first mixed perturbation operator An example is Figure 4 The vehicle in the example The initial route includes two one-way trips and one private car service trip. The initial route consists of two one-way trips. Then, try to move the vehicle The overall lines are inserted into the vehicle All possible 4 connections. Figure 4 As shown by the arrow in the figure, it is inserted into the connection between sequence number 8 and sequence number 21. If there are multiple feasible new routes, the one with the largest objective function is selected as the new solution. After operation, the vehicle The route has been changed, two new one-way trips have been added, and the vehicle The line was changed and became an empty line.

[0115] The second mixed perturbation operator Includes steps D1 to D3.

[0116] Step D1: In the vehicle set Randomly select two vehicles that have no or only one vehicle with a private car service and , where vehicles The path of is a non-empty feasible solution and Then, select the vehicle All one-way trips and vehicles All one-way travel connections.

[0117] Step D2: Check the vehicle All possible connections on both sides of the one-way trip will be Select any two adjacent one-way trips from the route and insert them into the vehicle At each connection, select the vehicles that meet the constraints 2 to 20. New line.

[0118] Step D3: If the vehicle All connections in the vehicle do not meet If the insertion condition of Return to vehicle collection In the process, a vehicle is randomly selected again and steps D1 to D2 are repeated until a new route is successfully generated, or the randomly generated vehicle exchange combinations fail to execute within the preset number of times. If the vehicle combination operator is executed successfully, the routes of the two exchanged vehicles are updated and the vehicles are deleted. , and then put the new line back into the vehicle collection;

[0119] In this embodiment, the second mixed perturbation operator An example is Figure 5 The vehicle in the example The initial route includes two one-way trips and one private car service trip. The initial route consists of three one-way trips. Then try to move the vehicle Two adjacent one-way trips 4 and 5 are respectively inserted into the vehicle All possible 4 connections. Figure 5 As shown by the arrow in the figure, it is inserted into the connection between sequence number 6 and sequence number 3. If there are multiple feasible new routes, the one with the largest objective function is selected as the new solution. After operation, the vehicle The line has added two one-way trips, and vehicles It then becomes a route with only one-way trip 3 left.

[0120] The third mixed perturbation operator Includes steps E1 to E3.

[0121] Step E1: At the vehicle assembly Randomly select two vehicles that have no or only one vehicle with a private car service and , where vehicles The path of is a non-empty feasible solution and Then, select the vehicle All one-way trips and vehicles All one-way travel connections.

[0122] Step E2: Check the vehicle and vehicles All two adjacent one-way trips in the route are swapped to obtain a new route for the two vehicles, and the vehicles that meet the constraints 2 to 20 are selected. and New line.

[0123] Step E3: Traverse the vehicles and vehicles If the adjacent one-way trips of two vehicles do not meet the interchange conditions and two feasible new routes cannot be generated, then Return to vehicle collection In the process, a vehicle is randomly selected again and steps E1 to E2 are repeated until a new route is successfully generated or all vehicle combinations fail to execute within the preset number of times. If the operator is executed successfully, the routes of the two vehicles are updated, and then the new routes of the two vehicles are put back into the vehicle set.

[0124] In this embodiment, the third mixed perturbation operator An example is Figure 6 The vehicle in the example The initial route includes two one-way trips and one private car service trip. The initial route consists of two one-way trips. Then try to move the vehicle Two adjacent one-way trips 3 and 4 and vehicles The two adjacent one-way strokes 3 and 4 are interchanged. Figure 6 As shown by the arrows in the figure, if there are multiple feasible new routes, the new solution is selected with the largest objective function. After operation, the vehicle The route has been updated with two one-way trips, and the vehicle The entire line is updated.

[0125] S5, according to the static scheduling model of inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, a local search operator based on the private car service passengers is set to improve the feasible solution after the disturbance.

[0126] In the embodiment of the present invention, based on the structural characteristics of feasible solutions in the route optimization problem of inter-city multi-trip round-trip vehicles integrating private car service and carpooling service, four local search operators based on private car service passengers are proposed to further improve the perturbed solution. Different from the hybrid perturbation operator, these four local search operators include not only the adjustment within the route but also the adjustment between the private car services of vehicles.

[0127] The passenger local search operator based on the private car service includes the first local search operator, the second local search operator, the third local search operator and the fourth local search operator. Represents the local search The designs of these four operators are introduced as follows.

[0128] First local search operator The method comprises step F1 and step F2.

[0129] Step F1: Randomly check the initial solution of vehicles and delete one passenger from the vehicle path in turn.

[0130] Step F2: After the vehicle deletes the passenger's boarding and alighting nodes, if the platform profit is higher than the undeleted state, the deletion operation is retained; if it is not higher than the original profit sum, it is not retained.

[0131] In this embodiment, the first local search operator An example is Figure 7 The vehicle in the example The initial route consists of two one-way trips and one private car service trip, and then attempts to transfer the vehicle The three one-way trips of are randomly deleted with passenger points. Figure 7 As shown by the arrows in the figure, if there are multiple feasible new routes, the new solution is selected with the largest objective function. After operation, the vehicle The line was updated with three one-way trips, reducing three passenger points.

[0132] Second local search operator Includes steps G1 to G3.

[0133] Step G1: Check whether unused vehicles can generate feasible routes using the current set of non-carpooling passengers.

[0134] Step G2: If possible, generate vehicle routes according to step A5, update the set of passengers who have not yet successfully carpooled and the routes of the vehicles. Then, randomly select a passenger from the vehicle route and delete it from the vehicle route and add it to the set of passengers who have not successfully carpooled. Find the position that can maximize the platform profit for the passengers who have successfully carpooled from all the routes of the vehicles and insert them.

[0135] Step G3: Select passengers who failed to carpool and insert them into their optimal vehicle positions, and update the set of passengers who failed to carpool.

[0136] In this embodiment, the second local search operator An example is Figure 8 As shown in the example, the set of passengers who did not participate in the carpooling failed to generate a feasible solution, and the vehicle Delete passenger sequence 2,7 and insert passenger 20 between passengers 22 and 23 in the private car service trip. Delete passenger sequence 13, insert passenger 8 between passenger 9 and passenger 0 in the one-way trip, and insert passenger 24 between passenger 26 and passenger 27 in the private car service trip. After operation, the vehicle and Three one-way trips were updated on each line.

[0137] The third local search operator Includes step H1 to step H2.

[0138] Step H1: A passenger is randomly selected from the set of passengers who have not successfully carpooled, and an insertion position is found for the passenger in all vehicle routes that have completed carpooling to increase the platform's profit.

[0139] Step H2: If inserting the failed carpooling passenger into the specified position can improve the original carpooling platform profit, then keep the insertion operation and update the vehicle set and the failed carpooling passenger set; otherwise, randomly select other passengers to perform .

[0140] In this embodiment, the third local search operator An example is Fig. 9As shown in the example, after randomly selecting the set of passengers who did not participate in the carpooling, the passenger sequence 12 is inserted into the first position of the one-way trip 1, the passenger sequence 20 is inserted between the passengers 22 and 23 of the private car service trip, and the passenger sequence 22 is inserted between the passengers 3 and 4 of the one-way trip 2. After operation, the vehicle The line has been updated with three one-way trips.

[0141] Fourth local search operator It includes step J1 and step J2, such as Fig.10 shown.

[0142] Step J1: Check from the vehicle's routes whether the trip of the private car service can exchange passenger routes with other one-way trips.

[0143] Step J2: If exchanging the passenger to the special car position can satisfy the constraints of formulas 2 to 20 and improve the profit of the original solution, then retain the insertion operation and update the set of passengers who failed to carpool; otherwise, randomly select other vehicles for testing.

[0144] S6, using a variable neighborhood search algorithm to solve the static scheduling model of inter-city multiple round-trip vehicles integrating the private car service and the carpooling service, the initial feasible solution, the neighborhood operator and the local search operator to obtain an optimal solution, wherein the optimal solution is a static scheduling plan.

[0145] The embodiment of the present invention fully combines the characteristics of the variable neighborhood search algorithm, designs a mixed perturbation operator with a larger neighborhood (i.e., a neighborhood operator based on a one-way trip) to search for the carpooling path, and designs a local search operator with a smaller neighborhood (i.e., a local search operator based on passengers of the private car service) to search for the private car service path and time suitable for each vehicle.

[0146] The variable neighborhood search algorithm mainly consists of two parts: variable neighborhood descent search (VND) and perturbation process (SHAKING). Step S6 specifically includes steps S61 to S68.

[0147] Step S61: Generate a random candidate solution from the neighborhood of the current state under the control of algorithm parameters.

[0148] Step S62: Perform neighborhood search in the variable neighborhood descent search process. If a solution better than the candidate solution is found, update the current solution and the global best solution, and continue searching the current neighborhood.

[0149] Step S63: If the current neighborhood search operator cannot find a better solution, the next neighborhood is searched.

[0150] Step S64: Repeat the above search process, and terminate the search when the number of iterations is reached or the termination variable neighborhood descent search condition is met.

[0151] Step S65: Perform neighborhood search during the perturbation process. If a solution better than the candidate solution is found, update the current solution and the global best solution, and continue searching the current neighborhood.

[0152] Step S66: If the current neighborhood perturbation operator cannot find a better solution, the next neighborhood is searched.

[0153] Step S67: Repeat the above search process, and terminate the search when the number of iterations is reached or the termination disturbance condition is met.

[0154] Step S68: End the search process and output the optimization result.

[0155] The static scheduling method of inter-city multiple round-trip vehicles integrating private car service and carpooling service of the present invention plans the multiple round-trip routes of inter-city online carpooling and the single period of private car service in the scenario of double-sided round-trip constraints with maximizing the sum of two kinds of vehicle profits as the optimization goal. The two modes of private car service and ordinary service are coupled with each other in the inter-city carpooling planning.

[0156] At the same time, the two-way carpooling problem and the problem of overall planning of the profit of the private car service performed by the vehicle during the idle period are considered. The two-stage algorithm represented by the approximate algorithm combined with the heuristic algorithm divides the problem into two sub-problems: generating the initial solution and searching for the optimal solution. The strong initial solution is generated by the approximate algorithm. Then the heuristic algorithm is used to optimize the iteration method to quickly search for the optimal solution, which is suitable for static scheduling problems with large data sets.

[0157] The sequential construction method is used on the initial feasible solution to generate one-way trips and carpooling routes. According to the characteristics of the problem model, three hybrid perturbation operators (i.e., neighborhood operators) for one-way trips are designed to perturb the current solution and four local search operators for private car services are designed to optimize the path and time of private car services. The static scheduling problem is optimized through different search frameworks and search operators, which effectively improves the convergence speed of complex problem models.

[0158] In order to verify the effectiveness of the method model and model solution proposed in the present invention, the application of the present invention will be illustrated with a practical example below. The passenger vehicle order data and GPS data from November 1, 2021 to November 30, 2021 in two adjacent cities in a certain place were selected for simulation. In order to analyze and verify the scheduling effects of various solution methods on the static scheduling model of inter-city multi-trip round-trip vehicles that integrates special car services and carpooling services of the present invention. Calculate the reservation order data for one week (including non-working days) respectively, and take the 7 solutions of the daily data to obtain the solutions of each experiment, and calculate the daily profit of the carpooling platform , Average driving time per vehicle , average waiting time for passengers , vehicle load factor, model convergence time and different solution methods are compared for verification. If these indicators are better than the comparison method or have a detailed improvement after optimization, the model method is verified to be correct.

[0159] The convergence criterion of the labeling module in the present invention adopts the principle of the maximum number of vehicles under the trip constraint. The convergence criterion of the genetic algorithm adopts the maximum number of iterations, and the encoding rule adopts the natural number encoding rule. The distance measurement parameter of the present invention and the comparison method is set to L1 distance, and the comparison model encoding rule is consistent. The experimental parameter settings are shown in Table 1.

[0160] Table 1 Experimental parameter settings

[0161]

[0162] The present invention respectively adopts a variable neighborhood search algorithm, a genetic algorithm with a unilateral strategy, a sequential construction method for maximizing platform profits, and a branch and bound method to test the proposed two-sided multi-trip round-trip carpooling path optimization problem model with special car service on a one-week carpooling reservation data.

[0163] Since the static scheduling model wants to improve the quality of carpooling services and increase the utilization rate of vehicle resources, according to the constraints of expanding the private car service, the number of passengers covered by the private car service of vehicles per day accounts for an average of less than 10% of the total passengers, and the planned time period is mostly from 13:00 to 17:00 in the afternoon. According to order data analysis, this period is in the off-peak period of inter-city carpooling.

[0164] Table 2 Comparison of total vehicle profit and average convergence time of each solution method

[0165]

[0166] Table 2 shows the total platform profit of the four methods and the convergence time of the model. In terms of the objective function value of the model, the solution method proposed in the present invention increases the total platform profit by an average of 8.07% compared with other methods. Among them, the total profit obtained by the branch and bound algorithm is the lowest. Compared with the inter-city carpooling path optimization problem with multiple round trips on both sides, the present invention uses a genetic algorithm with a unilateral strategy for comparison. It can be seen that the total profit is increased by an average of 7.76%. The reason for this may be that the proposed two-sided carpooling problem has increased the number of special car service orders compared to the one-sided carpooling problem, and the profit of this type of order is higher than that of ordinary orders.

[0167] Table 3 Comparison of average vehicle driving time and passenger waiting time for each solution method (unit: minutes)

[0168]

[0169] According to Table 3, the average driving time of vehicles in the model of the present invention is 2.52% higher than that of the comparison algorithm, and the average waiting time of passengers is shortened by 15.33% compared with that of the comparison algorithm.

[0170] Table 4 Comparison of average waiting time of passengers in each solution method

[0171]

[0172] According to Table 4, the initial solution generated by the model of the present invention accounts for more than 87.79% of the objective function value on average. The closer to the weekend, the lower the objective function value of the initial solution. Analysis of the problem shows that as the data scale increases, the deviation from the optimal solution becomes larger and larger when the approximate algorithm is used to solve the path. Analysis of the convergence time proportion of each part of the method in this chapter shows that the generation of the initial solution accounts for an average of 17.54% of the convergence time of the entire solution method, the mixed perturbation operator in the variable neighborhood algorithm accounts for an average of 15.14%, and the local search operator accounts for an average of 67.32%. Analysis shows that the local search operator is an internal search operator of the variable neighborhood search framework. If a search solution that is better than the current solution is encountered, the solution is updated and rolled back to search again.

[0173] Table 5 Comparison of average convergence time after missing a local search operator (unit: seconds)

[0174]

[0175] According to Table 5, reducing the participation of some local operators in the iterative search of the solution method can reduce the convergence time of the method. The local search operator with the greatest impact is . Analyzing the problem, we know The operator has higher tolerance than other operators, and more feasible solutions will enter the search of this operator.

[0176] In summary, the static scheduling method of inter-city multiple round trip vehicles integrating private car service and carpooling service of the present invention defines the concepts of one-way trip connection and private car service, and introduces the generation method of one-way trip and carpooling route on the initial feasible solution. Based on the static scheduling model of inter-city multiple round trip vehicles integrating private car service and carpooling service, three hybrid perturbation operators for one-way trip are designed to perturb the current solution and four local search operators for private car service are designed to optimize the path and time of private car service.

[0177] According to the experimental results, the method of the present invention is excellent and effective in solving the two-sided inter-city carpooling path optimization problem of integrated car-hailing services in terms of platform profit and convergence speed compared with the comparative algorithm. Finally, the present invention also conducts sensitivity analysis of different local operators on the designed variable neighborhood algorithm.

[0178] Embodiment 2: The present invention provides a static scheduling device for inter-city multiple round-trip vehicles integrating private car service and carpooling service, which comprises a data acquisition module, a model building module, an initial solution module, a neighborhood operator module, a local search operator module and a solution module.

[0179] The data acquisition module is used to acquire the passenger's scheduled travel data and vehicle set, wherein the scheduled travel data includes the first scheduled travel data of the private car service and the second scheduled travel data of the intercity carpooling service.

[0180] The model building module is used to build a static scheduling model for inter-city multi-trip round-trip vehicles integrating private car service and carpooling service based on the reservation travel data and the vehicle set, with maximizing the profit of ordinary carpooling and maximizing the profit of private car service as the optimization goal.

[0181] The initial solution module is used to generate an initial feasible solution using a sequential route construction algorithm based on the static scheduling model of the inter-city multi-trip vehicles integrating the private car service and the carpooling service. The initial feasible solution represents the maximum private car service time in the current one-way trip of the vehicle.

[0182] The neighborhood operator module is used to set a neighborhood operator based on a one-way trip according to the static scheduling model of the inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, so as to perturb the feasible solution of the current iteration.

[0183] The local search operator module is used to set a local search operator based on the passengers of the private car service according to the static scheduling model of the inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, so as to improve the feasible solution after the disturbance.

[0184] The solution module is used to solve the static scheduling model of the inter-city multiple round-trip vehicles integrating the private car service and the carpooling service, the initial feasible solution, the neighborhood operator and the local search operator using a variable neighborhood search algorithm to obtain an optimal solution. The optimal solution is a static scheduling plan.

[0185] Embodiment 3: The present invention provides a static dispatching device for inter-city multiple round trip vehicles integrating a private car service and a carpooling service, comprising a processor, a memory, and a computer program stored in the memory. The computer program can be executed by the processor to implement a static dispatching method for inter-city multiple round trip vehicles integrating a private car service and a carpooling service as described in any paragraph of Embodiment 1.

[0186] Embodiment 4: The present invention provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute a static scheduling method for multiple inter-city round-trip vehicles that integrates private car service and carpooling service as described in any paragraph of Embodiment 1.

Claims

1. A static dispatching method for multiple inter-city round trip vehicles integrating private car service and carpooling service, characterized in that: Include: Acquire the passenger's scheduled travel data and vehicle set; wherein the scheduled travel data includes first scheduled travel data for a private car service and second scheduled travel data for an intercity carpooling service; Based on the reservation travel data and the vehicle set, a static scheduling model for inter-city multiple round-trip vehicles integrating private car service and carpooling service is constructed with the optimization goal of maximizing the profit of ordinary carpooling and maximizing the profit of private car service; According to the static scheduling model of the inter-city multiple round-trip vehicles integrating the private car service and the carpooling service, an initial feasible solution is generated by using a sequential route construction algorithm; wherein the initial feasible solution represents the maximum private car service time in the current one-way trip of the vehicle; According to the static scheduling model of inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, a neighborhood operator based on a one-way trip is set to perturb the feasible solution of the current iteration; According to the static scheduling model of inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, a local search operator based on the private car service passengers is set to improve the feasible solution after the disturbance; According to the static scheduling model of the inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, the initial feasible solution, the neighborhood operator and the local search operator, a variable neighborhood search algorithm is used to solve and obtain an optimal solution; wherein the optimal solution is a static scheduling plan; The initial feasible solution is generated by using a sequential route construction algorithm; a one-way trip must be constructed first, and then the initial vehicle route solution is generated based on the one-way trip; Constructing a one-way trip includes steps A1 to A6; Step A1, traverse the passenger's reservation data and process each passenger one by one; Step A2: Update the passenger's starting point arrival time, determine the time window constraint, and continue to execute if the passenger's starting point arrival time meets the maximum tolerable time window condition; Step A3, updating the time when the passenger starts service at the starting point and adjusting the time schedule; Step A4: determine whether the number of passengers in the current trip is less than the given passenger capacity; Step A5, if not, use a greedy strategy based on maximizing revenue to transport the passengers in the current trip to their destinations and generate a one-way trip node vector; if yes, continue to process the next trip; Step A6, return to the one-way travel solution; Generating an initial feasible solution based on a one-way trip includes steps B1 to B6; Step B1, according to the steps of constructing a one-way itinerary, calculate the one-way itinerary of City A and City B; Step B2: Select the best one-way trip from the one-way trips of City A and City B as part of the current route; Step B3, obtaining the number of passengers on the route, and determining whether the number of passengers is less than or equal to 3; if the number of passengers is less than or equal to 3, planning the trip as a special car service route, otherwise planning it as a common service route; Step B4: remove the current trip node from the passenger set to prevent duplicate processing; Step B5: Update the vehicle route status according to the current trip node information; Step B6, return to the vehicle line node; According to the static scheduling model of the inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, the initial feasible solution, the neighborhood operator and the local search operator, a variable neighborhood search algorithm is used to solve and obtain the optimal solution, specifically including: Step S61: generating a random candidate solution from the neighborhood of the current state under the control of algorithm parameters; Step S62: performing neighborhood search in the variable neighborhood descent search process, if a solution better than the candidate solution is found, updating the current solution and the global best solution, and continuing to search the current neighborhood; Step S63: If the current neighborhood search operator cannot find a better solution, the next neighborhood is searched; Step S64: Repeat the above search process, and terminate the search when the number of iterations is reached or the termination variable neighborhood descent search condition is met; Step S65: Perform neighborhood search during the perturbation process. If a solution better than the candidate solution is found, update the current solution and the global best solution, and continue searching the current neighborhood. Step S66: If the current neighborhood perturbation operator cannot find a better solution, search the next neighborhood; Step S67: Repeat the above search process, and terminate the search when the number of iterations is reached or the termination disturbance condition is met; Step S68: End the search process and output the optimization result.

2. According to claim 1, a static dispatching method for multiple inter-city round-trip vehicles integrating a private car service and a carpooling service, characterized in that: The objective function of the static scheduling model for inter-city multi-trip vehicles integrating private car service and carpooling service is for: Objective function 1 represents maximizing revenue, which is the total fare of the completed ordinary carpooling service and private car service minus the vehicle path cost; in, The serial number of the travel reservation order for city A. The serial number of the travel reservation order for city B. is the set of reservation travel orders for cities A and B, is the program number, For all trips between cities A and B, For the normal carpool fare, is the first decision variable, Description of order Already Vehicle service for each trip, is the second decision variable, Description Order Already Vehicle service for each trip, For the itinerary collection from city A to departure, is the vehicle serial number, is a set of vehicles departing from cities A and B, The carpooling fare for the private car service, For itinerary The number of vehicles used for private car services, For itinerary The end time of the private car service period, For itinerary The start time of the private car service period, For trips departing from city B, For itinerary The number of vehicles used for private car services, For itinerary The end time of the private car service period, For itinerary The start time of the private car service period, For the Vehicle No. The pick-up and drop-off points for the outbound trip from city A to city B, and The serial numbers of the boarding and alighting points. express Point and The distance between points, and represents the passenger mileage cost, is the third decision variable, Explain the itinerary Vehicles from Click to Point passing, is the fourth decision variable, Explain the itinerary Vehicles from Click to point passing; The constraints of the static scheduling model for inter-city multi-trip vehicles integrating private car service and carpooling service are: Constraint 2 means that any vehicle in the departure trip must carry no more than X passengers and at least 1 passenger; Constraint 3 means that the departure passengers’ boarding time sequence must be arranged according to time; Constraint 4 is the time constraint that the departing passengers can tolerate the vehicle arriving early or late; Constraint 5 is the departure channel problem constraint: adjacent passengers in a passenger chain must satisfy the carpooling condition and also meet the vehicle travel time constraint from picking up the first passenger to the departure point; Constraint 6 is the departure detour coefficient constraint: the total distance traveled by the vehicle in the city divided by the distance from the first passenger to the departure point; Constraint 7 indicates that the departure time of the vehicle at any point is greater than or equal to the arrival time at that point; Constraint 8 means that the online ride-hailing service is guaranteed to provide services in the order of the vehicle paths of the trip; that is, the pick-up point is visited first and then the drop-off point, the pick-up point is before the entry and exit point of the starting city, and the drop-off point is after the entry and exit point of the destination city; Constraints 9 and 10 are used to ensure that the number of round trips between the two sides of the vehicle cannot exceed the maximum number of round trips between the two sides; Constraints 11 and 12 are used to ensure that the vehicle must rest for a certain period of time after completing a trip and before the next trip is available in the two-sided problem; Constraint 13 is used to ensure that when the vehicle's two-way round trip times reach the maximum, the next trip cannot be arranged; Constraint 14 means that the vehicle performs the special car service during the operation period, and the period is single and continuous; Constraint 15 means that the vehicle is allowed to have no special car service period, but must complete all daily inter-city tasks; Constraint 16 indicates that a vehicle can only perform a private car service once at most when traveling multiple times between cities in a day; Constraint 17 means that the number of passengers in the private car service of any vehicle in the trip departing from city A shall not exceed 3 and shall be at least 2; Constraint 18 means that a car can have multiple one-way trips but only one time slot of private car service; Constraint 19: The time for providing private car services in the two cities can be different; Constraint 20 indicates that the private car service is based on the passenger's scheduled boarding time; in, is the set of travel reservation orders for city A, is a set of positive integers, is the set of travel reservation orders for city B, Indicates Vehicles of trips arrived The moment of It means the difference between two elements. Indicates Vehicles of trips arrived The moment of is the increment of the serial number of the boarding and alighting point, Gathering for pick-up and drop-off points, is the trip number from city A to the departure point, Indicates Vehicles of trips arrived The moment of Indicates Vehicles of trips arrived The moment of is the trip number from city B, Indicates order The scheduled boarding time, For orders Maximum Tolerance Vehicle How long you arrive in advance? For orders Maximum Tolerance Vehicle The length of the delay, Indicates order The scheduled boarding time, For orders Maximum Tolerance Vehicle How long you arrive in advance? For orders Maximum Tolerance Vehicle The length of the delay, Assemble the intercity entry and exit points, It is the intercity entrance and exit point of city A. It is the intercity entrance and exit point of city B. Indicates The time when the vehicles of the trip arrive at the intercity entrance and exit point of city A, For the The time when the vehicles of the trip arrive at the intercity entrance and exit point of city B, For the The moment the journey ends, represents the maximum travel time constraint, Indicates The time when the vehicles of the trip arrive at the intercity entrance and exit point of city A, For the The time when the vehicles of the trip arrive at the intercity entrance and exit point of city B, For the The moment the journey ends, represents the detour constraint, For itinerary The distance of For itinerary The distance of For itinerary The distance of From the starting yard to the node The distance of For Node Distance to the final stop, Show itinerary Vehicle leaving The moment of Show itinerary Vehicle leaving The moment of Gather vehicles from city A, The serial number of the vehicle departing from city A, Indicates Number of round trips on both sides of the vehicle, Indicates Maximum number of two-way round trips per vehicle, Gather vehicles from city B, The serial number of the vehicle departing from city B, Indicates Number of round trips on both sides of the vehicle, Indicates Maximum number of two-way round trips per vehicle, For the The start time of the trip, For the The end time of the trip, For the The start time of the trip, For the The end time of the trip, Indicates vehicle Rest time, is the fifth decision variable, No vehicle is arranged No. Itinerary is the sixth decision variable, No vehicle is arranged No. Itinerary For vehicles The end time of the operating period, For vehicles The start time of the operating period, The serial number of the travel reservation order. The number of vehicles selected to provide chauffeur-driven services for vehicles on the trip, is the number of round trips, is the seventh decision variable, Private car service orders By itinerary Vehicle services, For private car service orders in City A, For a private car service order in city B.

3. According to claim 2, a static dispatching method for multiple inter-city round-trip vehicles integrating a private car service and a carpooling service is characterized in that: The neighborhood operator includes a first mixed perturbation operator, a second mixed perturbation operator and a third mixed perturbation operator; the perturbation operator is used to perturb the trip connection, and the trip connection refers to the place where the vehicle starting point is connected to the starting point of the first passenger in a single trip in any route of a feasible solution, or the place where the end point of the last passenger getting off in a trip is connected to the starting point of the first passenger in the next single trip; The first mixed perturbation operator Comprising steps C1 to C3; Step C1: Gather at the vehicle Randomly select two vehicles that have no or only one vehicle with a private car service and , where vehicles The path of is a non-empty feasible solution and ; First, select the vehicle All one-way trips and vehicles included All one-way travel connections; Step C2: Check the vehicle All possible connections and put the vehicle All one-way trips on the route are inserted into the vehicle as a whole At each connection, select the vehicles that meet the constraints 2 to 20. New lines; Step C3: If the vehicle All connections in the vehicle do not meet If the insertion condition of Return vehicle set In the process, a vehicle is randomly selected again and steps C1 to C2 are repeated until a new route is successfully generated or all possible vehicle combinations fail within the preset number of times. If the operation is successful, the routes of the corresponding two vehicles are updated and the vehicle is deleted. , and then put the new line back into the vehicle set; The second mixed perturbation operator comprising steps D1 to D3; Step D1: In the vehicle set Randomly select two vehicles that have no or only one vehicle with a private car service and , where vehicles The path of is a non-empty feasible solution and ; Then, select the vehicle All one-way trips and vehicles All one-way connections; Step D2: Check the vehicle All possible connections on both sides of the one-way trip will be Select any two adjacent one-way trips from the route and insert them into the vehicle At each connection, select the vehicles that meet the constraints 2 to 20. New lines; Step D3: If the vehicle All connections in the vehicle do not meet If the insertion condition of Return to vehicle collection In the process, a vehicle is randomly selected again and steps D1 to D2 are repeated until a new route is successfully generated, or the randomly generated vehicle exchange combinations fail to execute within the preset number of times. If the vehicle combination operator is executed successfully, the routes of the two exchanged vehicles are updated and the vehicles are deleted. , and then put the new line back into the vehicle collection; The third mixed perturbation operator Comprising steps E1 to E3; Step E1: At the vehicle assembly Randomly select two vehicles that have no or only one vehicle with a private car service and , where vehicles The path of is a non-empty feasible solution and ; Then, select the vehicle All one-way trips and vehicles All one-way connections; Step E2: Check the vehicle and vehicles All two adjacent one-way trips in the route are swapped to obtain a new route for the two vehicles, and the vehicles that meet the constraints 2 to 20 are selected. and New lines; Step E3: Traverse the vehicles and vehicles If the adjacent one-way trips of two vehicles do not meet the interchange conditions and two feasible new routes cannot be generated, then Return to vehicle collection In the process, a vehicle is randomly selected again and steps E1 to E2 are repeated until a new route is successfully generated or all vehicle combinations fail to execute within a preset number of times; if the operator is executed successfully, the routes of the two vehicles are updated, and then the new routes of the two vehicles are put back into the vehicle set.

4. According to claim 2, a static dispatching method for multiple inter-city round-trip vehicles integrating a private car service and a carpooling service is characterized in that: The local search operators include a first local search operator, a second local search operator, a third local search operator and a fourth local search operator; First local search operator Comprising step F1 and step F2; Step F1: randomly check the initial solution of the vehicle and delete one passenger from the vehicle path in turn; Step F2: After the vehicle deletes the boarding and alighting nodes of the passenger, if the platform profit is higher than the undeleted state, the deletion operation is retained; if it is not higher than the original profit sum, it is not retained; Second local search operator Comprising steps G1 to G3; Step G1: Check whether unused vehicles can generate feasible routes using the current set of non-carpooling passengers; Step G2: if possible, generate the vehicle route according to step A5, and update the set of passengers who have not yet successfully shared the car and the vehicle route; Then, the passengers of any vehicle are removed from the vehicle route and added to the set of passengers who failed to carpool; Passengers who have not successfully shared a ride are inserted into the routes of all the vehicles that have shared a ride, in a position that can maximize the platform's profits; Step G3: Select the passengers who failed to carpool and insert them into their optimal vehicle positions, and update the set of passengers who failed to carpool; The third local search operator Comprising steps H1 to H2; Step H1: Randomly select a passenger from the set of passengers who have not successfully carpooled, and find an insertion position for the passenger in all vehicle routes that have completed carpooling to increase the platform's profit; Step H2: If inserting the failed carpooling passenger into the specified position can improve the original carpooling platform profit, then keep the insertion operation and update the vehicle set and the failed carpooling passenger set; otherwise, randomly select other passengers to perform ; Fourth local search operator Comprising step J1 and step J2; Step J1: Check from the vehicle's route whether the trip of the private car service can exchange passenger routes with other one-way trips; Step J2: If exchanging the passenger to the special car position can satisfy the constraints of formulas 2 to 20 and improve the profit of the original solution, then retain the insertion operation and update the set of passengers who failed to carpool; otherwise, randomly select other vehicles for testing.

5. A static dispatching method for multiple inter-city round-trip vehicles integrating a private car service and a carpooling service according to any one of claims 1 to 4, characterized in that: The reserved travel data is the reserved travel information provided by the passenger to the carpooling platform in advance; the reserved travel information includes the passenger's designated boarding point and alighting point, and the agreed time for the passenger to board the vehicle; set up represents the set of reservation travel orders for cities A and B. is the set of travel reservation orders in city A. is the serial number of the travel reservation order for city A. is the total number of travel reservation orders in city A, is the set of travel reservation orders for city B. is the serial number of the travel reservation order for city B. is the total number of travel reservation orders in city B; set up For the Multiple round trips of vehicles to gather at the boarding and alighting points, For the Vehicle No. The pick-up and drop-off points for the outbound trip from city A to city B are gathered. The numbered set of boarding points for passengers in city A. For city A A pick-up point. The numbered set of passengers' drop-off points in city B, For city B drop-off points; For the Vehicle No. The pick-up and drop-off points for the return trip from city B to city A are gathered. The numbered set of boarding points for passengers in city B, For city B A pick-up point. The numbered set of passengers' drop-off points in city A, For city A drop-off points; The first scheduled trip data of the private car service is the private car service provided by some vehicles during the private car service period. A vehicle has at most one single and continuous private car service period; The number of passengers that the vehicle can carry during the special car service period is not greater than the first preset value; The first preset value is half of the maximum passenger capacity of the vehicle, rounded down; The vehicle is configured to be able to carry multiple trips; the multiple trips include at least two single trips in opposite directions; wherein the single trip refers to a single trip from city A to city B, or a single trip from city B to city A; each multiple trip can also only be served by one vehicle, that is, one vehicle corresponds to multiple single trips, and each single trip can only be served by one vehicle; set up is the set of all itineraries between cities A and B, is the set of trips from city A to departure. is the trip number from city A to the departure point, Represents the total number of trips from city A to city B, For the itinerary set starting from city B, is the trip number from city B, Represents the total number of trips from city B to city A; set up For the vehicle collection Contains the vehicle set of city A and city B, Gather vehicles from city A. is the serial number of the vehicle departing from city A, represents the total number of vehicles departing from city A, Gather vehicles from city B. is the serial number of the vehicle departing from city B, Represents the number of vehicles in city B.

6. A static dispatching device for multiple inter-city round trip vehicles integrating private car service and carpooling service, characterized in that: Include: A data acquisition module, used to acquire the passenger's scheduled travel data and vehicle set; wherein the scheduled travel data includes the first scheduled travel data of the private car service and the second scheduled travel data of the intercity carpooling service; A model building module is used to build a static scheduling model for inter-city multiple round-trip vehicles integrating private car service and carpooling service based on the reservation travel data and the vehicle set, with maximizing the profit of ordinary carpooling and maximizing the profit of private car service as the optimization goal; An initial solution module, for generating an initial feasible solution by using a sequential route construction algorithm according to the static scheduling model of the inter-city multi-trip round-trip vehicle integrating the private car service and the carpooling service; wherein the initial feasible solution represents the maximum private car service time in the current one-way trip of the vehicle; A neighborhood operator module is used to set a neighborhood operator based on a one-way trip according to the static scheduling model of the inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, so as to perturb the feasible solution of the current iteration; A local search operator module is used to set a local search operator based on passengers of the private car service according to the static scheduling model of the inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, so as to improve the feasible solution after the disturbance; A solution module, for solving the static scheduling model of the inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, the initial feasible solution, the neighborhood operator and the local search operator, using a variable neighborhood search algorithm to obtain an optimal solution; wherein the optimal solution is a static scheduling plan; The initial feasible solution is generated by using a sequential route construction algorithm; a one-way trip must be constructed first, and then the initial vehicle route solution is generated based on the one-way trip; Constructing a one-way trip includes steps A1 to A6; Step A1, traverse the passenger's reservation data and process each passenger one by one; Step A2: Update the passenger's starting point arrival time, determine the time window constraint, and continue to execute if the passenger's starting point arrival time meets the maximum tolerable time window condition; Step A3, updating the time when the passenger starts service at the starting point and adjusting the time schedule; Step A4: determine whether the number of passengers in the current trip is less than the given passenger capacity; Step A5, if not, use a greedy strategy based on maximizing revenue to transport the passengers in the current trip to their destinations and generate a one-way trip node vector; if yes, continue to process the next trip; Step A6, return to the one-way travel solution; Generating an initial feasible solution based on a one-way trip includes steps B1 to B6; Step B1, according to the steps of constructing a one-way itinerary, calculate the one-way itinerary of City A and City B; Step B2: Select the best one-way trip from the one-way trips of City A and City B as part of the current route; Step B3, obtaining the number of passengers on the route, and determining whether the number of passengers is less than or equal to 3; if the number of passengers is less than or equal to 3, planning the trip as a special car service route, otherwise planning it as a common service route; Step B4: remove the current trip node from the passenger set to prevent duplicate processing; Step B5: Update the vehicle route status according to the current trip node information; Step B6, return to the vehicle line node; According to the static scheduling model of the inter-city multi-trip round-trip vehicles integrating the private car service and the carpooling service, the initial feasible solution, the neighborhood operator and the local search operator, a variable neighborhood search algorithm is used to solve and obtain the optimal solution, specifically including: Step S61: generating a random candidate solution from the neighborhood of the current state under the control of algorithm parameters; Step S62: performing neighborhood search in the variable neighborhood descent search process, if a solution better than the candidate solution is found, updating the current solution and the global best solution, and continuing to search the current neighborhood; Step S63: If the current neighborhood search operator cannot find a better solution, the next neighborhood is searched; Step S64: Repeat the above search process, and terminate the search when the number of iterations is reached or the termination variable neighborhood descent search condition is met; Step S65: Perform neighborhood search during the perturbation process. If a solution better than the candidate solution is found, update the current solution and the global best solution, and continue searching the current neighborhood. Step S66: If the current neighborhood perturbation operator cannot find a better solution, search the next neighborhood; Step S67: Repeat the above search process, and terminate the search when the number of iterations is reached or the termination disturbance condition is met; Step S68: End the search process and output the optimization result.

7. A static dispatching device for multiple inter-city round trip vehicles integrating private car service and carpooling service, characterized in that: It includes a processor, a memory, and a computer program stored in the memory; the computer program can be executed by the processor to implement a static scheduling method for multiple inter-city round-trip vehicles that integrates private car service and carpooling service as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute a static scheduling method for multiple inter-city round-trip vehicles that integrates private car service and carpooling service as described in any one of claims 1 to 5.

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