JP6999882B2 - Optimal route determination device and optimum route determination program - Google Patents

Description

The present invention determines the optimum route that realizes complicated business state management, facilitates recalculation of the delivery plan, and easily moves to the next delivery destination in consideration of the actual environment of the delivery destination. It relates to an optimum route determination device and an optimum route determination program that can be used.

Conventionally, in the field of "combinatorial optimization", mainly "modeling a problem in the real world into a combinatorial optimization problem" and "developing a solution to a certain combinatorial optimization problem" have been studied. Then, among the combinatorial optimization problems, there is a problem called "vehicle routing problem (VRP)". This is the length of the route within the route of the vehicle (order of visits) such that when multiple vehicles and multiple destinations are entered, all the destinations are visited exactly once by one of the vehicles. It is a problem to find the one that minimizes the sum of. For decades, a number of problems that incorporate the constraints that appear in reality for VRP have been proposed, and approximate solutions to them have also been studied at the same time.
In addition, there is a problem called "PDP: pickup and delivery problem" as a generalized problem of VRP. This is based on the order that when multiple sets of destinations to load luggage and destinations to unload the luggage are entered, the same vehicle visits each destination for each group, and then unloads after loading. It is a problem to find the route of the vehicle that the total length of the route is the minimum among the routes of the vehicles in which all the destinations are visited exactly once by one of the vehicles. Similar to VRP, PDP has proposed a number of problems that incorporate constraints that appear in reality, and approximate solutions to them have also been studied at the same time.

For example, Patent Document 1 describes a plurality of delivery plans determined by a grouping process of allocating delivery destinations to each vehicle and a route optimization process of order in which vehicles travel around the delivery destination group determined by grouping. A technique is disclosed in which multiple delivery plans are generated using the grouping strategy of, and the optimum delivery plan is selected among them.

Japanese Unexamined Patent Publication No. 2001-188984

By the way, in VRP and PDP, it is general that only one place representing the destination is considered as the point information of the visited place. When finding the shortest route to visit multiple destinations, the shortest route is calculated on the premise that the shortest route connecting the points representing each destination is simply connected, so the direction of arriving at a certain destination is determined. U-turns may occur due to different directions of departure from the destination. If the road is a road that is very difficult to make a U-turn and takes time, there is a possibility that the shortest route should have been sought, but it will take time. In addition, there is a problem that the shortest path calculation is not taken into consideration even though there is a more suitable stop position at the visited destination.

In addition, there are cases where a single vehicle is responsible for performing complicated tasks from the collection of packages to the completion of delivery, and in a situation where we are planning to perform multiple such complex tasks. If a sudden interruption work occurs or a work is canceled, there is a problem that the delivery plan of the vehicle is greatly collapsed. In particular, it is not easy to manage which task of a complicated task composed of a plurality of tasks is completed, and there is a problem that it is difficult to recalculate the delivery plan. As a result, there is a problem that the burden on the driver of the vehicle is increasing because the driver accepts and responds to the change from the original delivery plan as it is.

The present invention has been made in view of the above problems, realizes complicated business state management, facilitates recalculation of the delivery plan, and considers the actual environment of the delivery destination to the next delivery destination. It is an object of the present invention to provide an optimum route determination device and an optimum route determination program capable of determining an optimum route that can easily move to.

The optimum route determination device according to the present invention is an optimum route determination device for determining an optimum route for movement when continuously processing a plurality of services executed at different points, and the plurality of services. A service-specific information acquisition unit that acquires service-specific information including execution point information for each, an execution order determination unit that combines execution orders for the plurality of services and calculates them as an optimization problem to determine the execution order, and the above-mentioned Using the execution point-specific information acquisition unit that acquires execution point-specific information including information of at least one stop position candidate at the execution point of each service for each of the plurality of services, and the execution order and the execution point-specific information. It is characterized by including an optimum route determination unit for determining an optimum route including information on an optimum stop position and / or an optimum stop direction at each execution point.

Further, in the optimum route determination device according to the present invention, the execution point-specific information further includes peripheral cost information including a U-turn cost value at the execution point of each service, and the optimum route determination unit is for each route. The peripheral cost information is used to calculate the total cost value required for the movement in, and the total cost value of each of the plurality of routes is used to determine the optimum route.

Further, the optimum route determination device according to the present invention is a job status management unit that updates a status management table for managing the status of a job composed of at least one related service according to a change in the status of the job. Further, the execution order determination unit acquires the state information of the job by referring to the state management table, identifies the service that needs to be executed from the state information of the job, and provides a service for the specified service. It is characterized in that specific information is acquired and the execution order is determined based on the acquired service specific information.

Further, in the optimum route determination device according to the present invention, the state management table handles the work of delivering the target picked up by the vehicle to a predetermined position as a unit of one job, and the state of the job is (A) the vehicle. Before loading on (planned to be loaded in this plan), (B) before loading on vehicle (not planned to be loaded in this plan), (C) before unloading from vehicle (planned to be unloaded in this plan), (D) unloading from vehicle The five target states of the previous (not planned to be unloaded in this plan) and (E) after being unloaded from the vehicle, and the states in the two plans of (F) with the allocation destination vehicle and (G) without the allocation destination vehicle. The job status is managed by a combination of these, and when the execution order determination unit receives a predetermined recalculation execution instruction, the job status information is obtained with reference to the status management table. It is characterized in that the service that needs to be executed is specified based on the state information of the job that is acquired and different from the plan before recalculation, and the execution order is determined for the specified service.

The optimum route determination program according to the present invention is an optimum route determination program for allowing a computer to realize a process of determining an optimum route for movement when continuously processing a plurality of services executed at different points. Then, the computer is combined with the service specific information acquisition function that acquires the service specific information including the execution point information for each of the plurality of services, and the execution order of the plurality of services is combined and calculated as an optimization problem, and the execution order is calculated. Execution order determination function for determining execution point, execution point specific information acquisition function for acquiring execution point specific information including information of at least one stop position candidate at the execution point of each service for each of the plurality of services, and the execution order. It is characterized by realizing an optimum route determination function for determining an optimum route including information on an optimum stop position and / or an optimum stop direction at each execution point by using the information specific to the execution point.

According to the present invention, it is possible to determine the optimum route in consideration of the stop position and the stop direction by considering a plurality of stop position candidates when determining the optimum route. In addition, when determining the execution order, it is possible to check the job status information in the status management table, extract the services that need to be executed, and then determine the execution order. That is, even if the vehicle has already started moving and the plan is being executed, it is possible to acquire the status information of the job at that time and recalculate the execution order.

It is a block diagram which showed the structure of the whole system for realizing the optimum route determination apparatus which concerns on this invention. It is explanatory drawing which showed an example of the structure of the optimum route determination apparatus (server apparatus) 10 which concerns on this invention. It is explanatory drawing which showed an example of the state of a job in the state management table managed by the optimum route determination apparatus 10 which concerns on this invention. It is a flowchart which showed the flow of the whole processing in the optimum route determination apparatus 10 which concerns on this invention. It is a flowchart which showed the flow of the execution order determination process in the optimum route determination apparatus 10 which concerns on this invention. It is a flowchart which showed the flow of the optimum route determination processing in the optimum route determination apparatus 10 which concerns on this invention. It is explanatory drawing for demonstrating the flow of job state management and recalculation. It is explanatory drawing for demonstrating the flow of job state management and recalculation. It is explanatory drawing for demonstrating the flow of job state management and recalculation. It is explanatory drawing for demonstrating the flow of job state management and recalculation. It is explanatory drawing for demonstrating the flow of job state management and recalculation. It is explanatory drawing for demonstrating the state of the optimal route determination. It is explanatory drawing for demonstrating the state of the optimal route determination. It is explanatory drawing for demonstrating the state of the optimal route determination.

[First Embodiment]
Hereinafter, an example of the optimum route determination device according to the first embodiment will be described with reference to the drawings. FIG. 1 is a block diagram showing the configuration of the entire system for realizing the optimum route determination device according to the present invention. The optimum route determination device 10 may be a device designed as a dedicated machine, but it is assumed that the optimum route determination device 10 can be realized by a general computer or a server device. In this case, the optimum route determination device 10 includes a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), and a memory that a general computer or server device would normally have. , It is assumed that it is equipped with storage such as a hard disk drive (not shown). Further, it goes without saying that various processes are executed by the program in order to make these general computers and server devices function as the optimum route determination device 10 of this example.

As shown in FIG. 1, the configuration of the entire system for realizing the optimum route determination device includes the server device 10 and the service executor terminals 201 to 20n (hereinafter, these are collectively referred to as the service executor terminal 20). (Including) and the headquarters terminal 30 are configured to be connectable to each other via the communication network 40. Of these, the case where the server device 10 functions as the optimum route determination device 10 of this example will be described as an example.

FIG. 2 is an explanatory diagram showing an example of the configuration of the optimum route determination device (server device) 10 according to the present invention. As shown in FIG. 2, the optimum route determination device 10 includes a job state management unit 11, a service specific information acquisition unit 12, a vehicle position information acquisition unit 13, an execution order determination unit 14, and execution point-specific information acquisition. A unit 15, an optimum route determination unit 16, and a storage unit 17 are provided at least.

The job status management unit 11 has a function of updating a status management table for managing the status of a job composed of at least one related service according to a change in the status of the job. Here, in this example, a job means a business composed of at least one related service. Further, in this example, the service refers to a unit for separating work that requires work to be performed by stopping (stopping) a moving body such as a vehicle. As an example, if a job is to collect a package at a certain point and deliver it to another point, the job is composed of a pickup service (pickup service) and a delivery service (delivery service). The status management table is a table for managing the status of jobs.

FIG. 3 is an explanatory diagram showing an example of a job state in a state management table managed by the optimum route determination device 10 according to the present invention. As shown in FIG. 3, taking the case where the above-mentioned delivery work is considered as a job as an example, the job states are (A) before being mounted on the vehicle (planned to be loaded in this plan) and (B) before being mounted on the vehicle. (No plan to load in this plan), (C) Before unloading from vehicle (planned to unload in this plan), (D) Before unloading from vehicle (not planned to unload in this plan), (E) After unloading from vehicle It has the state of the target (luggage) in the five realities and the state in the two plans of (F) with the allocation destination vehicle and (G) without the allocation destination vehicle, and manages the job state by combining these. It shall be. Here, this plan means an initial plan planned in advance before the vehicle departs. On the other hand, the plan may be changed in the middle, and the changed plan shall be expressed as the current plan. The status management table may be updated by any means as long as the status of the job can be managed. For example, every time the status of the job changes, the service execution possessed by the service executor itself is executed. A configuration is conceivable in which the status management table is updated by transmitting the job status information input to the personal terminal 20 to the optimum route determination device (server device) 10 via the communication network 40.

The service specific information acquisition unit 12 has a function of acquiring service specific information including information on execution points for each of a plurality of services. Service-specific information refers to information necessary to specify the content of the service to be executed. The execution point is a position where the service is executed. Each of at least one service constituting the job has an execution point, and the information on the execution point can be said to be one of the service specific information. Further, as the service specific information, various information such as the personal information of the client and the specific content information of the service can be considered.

The vehicle position information acquisition unit 13 has a function of acquiring vehicle position information indicating the current position of the vehicle used by the service executor. Any means may be used as long as the vehicle position information can be acquired, but for example, the GPS information of the vehicle may be acquired.

The execution order determination unit 14 has a function of combining execution orders for a plurality of services and calculating as an optimization problem to determine the execution order. More specifically, the execution order determination unit 14 acquires job status information by referring to the status management table, identifies the service that needs to be executed from the job status information, and acquires service specific information for the identified service. It also has a function to determine the execution order based on the acquired service specific information. By referring to the status management table, it is possible to grasp the status of the job, and as a result, it is possible to specify which of the services constituting the job needs to be executed. After specifying the service that needs to be executed, the service specific information is acquired for the specified service, and the execution order is determined based on the acquired service specific information. Execution order determination shall be based on algorithms for known combinatorial optimization problems such as VRP and PDP.

Further, as a premise that the execution order determination unit 14 determines the execution order, the vehicle position information acquisition unit 13 acquires the vehicle position information of the vehicle used by the service executor, and determines the execution order with the vehicle position as the starting point. To prepare for. In other words, when planning in advance before the vehicle departs, the execution order is to set the place where the vehicle is to wait (head office position, parking lot position, etc.) as the departure point and return point, but the vehicle is a service. The vehicle position information is important information because the execution order changes depending on the position of the vehicle when it becomes necessary to change the plan during the execution of the above.

That is, the fact that the vehicle position information can be acquired and the execution order can be determined means that the execution order can be recalculated at any timing. Therefore, when a job is canceled or an additional job occurs, it is necessary to calculate the execution order in a state different from the present plan. The recalculation may be performed based on an instruction from the service executor or the headquarters, or may be performed automatically at the timing when the job status changes or periodically.

Further, the execution order determination unit 14 may execute the execution order determination process in each of a plurality of situations such as changing the parameters to hold the solution of the execution order of the plurality of patterns. Here, as an example of generating a solution of a plurality of patterns, a pattern set in a short time with the required time required for movement as a parameter, a pattern set in a standard time, a pattern set in a long time, and the like are generated. Can be mentioned. Depending on the actual traffic conditions, the time required for traveling may be shorter or longer than the standard time, so by holding multiple patterns, it is possible to change the schedule on the way. Also, when the plan progresses after the solution of the execution order is generated and the state of the job changes, the previously created solution cannot be used as it is. In that case, it can be used by performing the following conversion. Focusing on the job status, the pick-up service and delivery service are removed from the solution for jobs whose current status is B, D, or E. If the original solution changed from A to C, the pickup service is removed from the solution. Then, the starting point is replaced with the current position of the vehicle. The above makes it possible to convert to the current solution. However, the route can be inefficient. Also, it is not always feasible. By combining the retention of such a plurality of patterns of solutions and the restoration of solutions, it is possible to respond to changes in the situation. For example, if you have a pattern with fast movement and a pattern with slow movement, and if you are operating in a fast pattern and there is a delay, you can switch to a slow pattern. Since the previous solution is an efficient solution, it can be expected that the solution without the executed service is also a good solution to some extent (it is a combination of those that are partially good routes). However, considering the current position, it may be wasteful, so it is expected that recalculating the restored solution as the initial solution will give a faster and better solution than calculating the solution of the slow pattern from scratch. Will be done.

The execution point-specific information acquisition unit 15 has a function of acquiring execution point-specific information including information of at least one stop position candidate at an execution point of each service for each of a plurality of services. Here, the execution point-specific information refers to information specific to the vicinity of the execution point of the service that can be used to determine the optimum route. Further, the stop position candidate information refers to information on a position that is a candidate for stopping the vehicle around the execution point. The execution point-specific information may be stored in advance by the creator of the information in association with the execution point, or information that may be related to the execution point is automatically associated and stored. May be.

Further, the execution point-specific information may include peripheral cost information including a U-turn cost value at the execution point of each service. Here, the peripheral cost information refers to the information necessary for calculating the cost information of the service execution point. An example of peripheral cost information is the cost value of a U-turn. If the arrival direction and the departure direction for the stop position candidate around the execution point are different, it is necessary to make a U-turn at the stop position candidate point. If it is a place where a U-turn can be easily performed, set a small cost value, and if it is a place where it is not easy to make a U-turn, set a large cost value. Such peripheral cost information is used to calculate the total cost value of each route and determine the route having a small cost value as the optimum route. For example, a method that determines only by the shortest travel distance requires a U-turn, but if the U-turn is a very difficult place, the distance is the shortest, but the required time is long. There is a risk that it will end up. In this way, by using the peripheral cost information, it is possible to determine the optimum route by using information other than the distance. Further, as peripheral cost information, a cost value may be set for a road used as a route. In other words, it is conceivable to adjust the cost value for road selection, such as setting a high cost value for roads that take a long time to move because the road width is narrow and the speed cannot be increased.

The optimum route determination unit 16 has a function of determining an optimum route including information on the optimum stop position and / or the optimum stop direction at each execution point by using the execution order and the information peculiar to the execution point. Further, the optimum route determination unit 16 uses peripheral cost information to calculate the total cost value required for movement in each route, and has a function of using the total cost value of each of the plurality of routes to determine the optimum route. Have. Specifically, for example, from the number of stop position candidates at each execution point, the arrival direction information for each stop position candidate, and the departure direction information from each stop position candidate, the options at each execution point can be selected. It is determined. Then, a route suitable for the determined option is selected. The travel distance is calculated and the cost value is calculated for all routes. The route with a short travel distance and a low cost value is determined as the optimum route. It is possible to appropriately set how to determine the optimum route by adopting the evaluation of the travel distance and the evaluation of the cost value. The determined optimum route is transmitted to the service executor terminal 20 and / or the headquarters terminal 30 via the communication network 40.

The storage unit 17 has a function of storing data necessary for various processes performed in the optimum route determination device 10 and data obtained as a result of the processes.

Next, the flow of the entire process in the optimum route determination device 10 according to the present invention will be described. FIG. 4 is a flowchart showing the flow of the entire process in the optimum route determination device 10 according to the present invention. As shown in FIG. 4, the processes in the optimum route determination device 10 include a process of acquiring information on the job to be handled (step S101), an execution order determination process for each service in which the job is divided (step S102), and a service. It is configured to execute the optimum route determination process (step S103) including the information of the optimum stop position for each execution point. Hereinafter, the execution order determination process and the optimum route determination process will be described in detail.

FIG. 5 is a flowchart showing the flow of execution order determination processing in the optimum route determination device 10 according to the present invention. As shown in FIG. 5, the execution order determination process is started by acquiring the information of the job handled by the optimum route determination device 10 (step S201). The optimum route determination device 10 divides each job into component services (extracts services constituting the job) (step S202). The optimum route determination device 10 collates all services of all jobs with job status information and determines services that need to be executed (step S203). Next, the optimum route determination device 10 acquires the current position information of the vehicle (step S204). The optimum route determination device 10 calculates a combinatorial optimization problem (VRP and PDP) for services that need to be executed, using the acquired current position of the vehicle as a starting point (step S205). Then, the optimum route determination device 10 outputs the execution order obtained by solving the combinatorial optimization problem (VRP and PDP) (step S206), and ends the process.

FIG. 6 is a flowchart showing the flow of the optimum route determination process in the optimum route determination device 10 according to the present invention. As shown in FIG. 6, the optimum route determination process is started by acquiring information on the execution order of services in the optimum route determination device 10 (step S301). Next, the optimum route determination device 10 acquires execution point-specific information including at least one stop position candidate information and peripheral cost information at the execution point of each service (step S302). Then, the optimum route determination device 10 determines and outputs the optimum route including the optimum stop position and the optimum stop direction using the information peculiar to the execution point (step S303), and ends the process.

Next, the flow of job state management and recalculation will be described in more detail based on the drawings. 7 to 11 are explanatory diagrams for explaining the flow of job state management and recalculation. FIG. 7A shows the execution points of the services constituting each of the four jobs on a map, and shows how the execution order is determined in this situation. Job 1 is composed of pick-up service P1 and delivery service D1, similarly, job 2 is composed of P2 and D2, job 3 is composed of P3 and D3, and job 4 is composed of P4 and D4, respectively. It is assumed that the pick-up and delivery of each job does not need to be performed continuously. In addition, since each job is in a state where the vehicle is on standby at the vehicle base, all the jobs are (A) before being mounted on the vehicle (planned to be loaded in this plan), and (F) there is an assigned vehicle. It shall be in a state. The vehicle determines the execution order when the vehicle departs from the vehicle base (depot), executes all services, and then returns to the vehicle base (depot) again. As a result of calculation and determination as a combinatorial optimization problem, it is assumed that the execution order is determined so as to execute in the order of depot, P1, P2, D1, D2, P3, D3, P4, D4, and depot. The vehicle starts executing the service with the execution order determined as shown in FIG. 7A as the main plan.

FIG. 7B shows a state in which the pickup service P1 of job 1 is completed. When the service executor terminal 20 inputs that P1 for job 1 has been completed, the status management table is updated, and as shown in FIG. 7B, the status related to job 1 is before being unloaded from the vehicle (C). It will be updated to (planned to be taken down in this plan).

FIG. 8A shows a state in which the job 4 is canceled while the vehicle is moving for the next execution of P2 after the completion of P1. As shown in FIG. 8A, the state management table is updated, and the state of job 4 is updated before (B) being loaded on the vehicle (not planned to be loaded in this plan). FIG. 8B shows a state in which the pickup service P2 of the job 2 is completed thereafter. When the service executor terminal 20 inputs that P2 for job 2 has been completed, the status management table is updated, and as shown in FIG. 8B, the status related to job 2 is before being unloaded from the vehicle (C). It will be updated to (planned to be taken down in this plan).

FIG. 9A shows a state in which job 1 is canceled while the vehicle is moving for the next execution of D1 after the completion of P2. As shown in FIG. 9A, the state management table is updated, and the state of job 1 is updated before (D) being unloaded from the vehicle (not planned to be unloaded in this plan). FIG. 9B shows a state in which job 1 is canceled while the vehicle is moving for the next execution of D1 after the completion of P2. In the situation of FIG. 9B, the execution order determination shall be recalculated.

FIG. 10A shows the recalculation result for the execution order determination.
Determine the order of execution when departing from the vehicle's current location as the starting point, executing the remaining services that need to be executed, and then returning to the vehicle base (depot). At this time, job 1 and job 4 whose states are B and D are excluded as services that do not need to be executed. As a result of calculation and determination as a combinatorial optimization problem, it is assumed that the execution order is determined so as to execute in the order of the current location, P3, D3, D2, and depot.

FIG. 10 (b) represents a pre-stage to restore the original plan held prior to departure based on the recalculation results obtained in FIG. 10 (a). The original plan shown in FIG. 10 (b) shall be restored based on the current job status and the current position of the vehicle shown in FIG. 10 (b).

FIG. 11 shows the result of restoring the original plan held before departure based on the recalculation result obtained in FIG. 10 (a). With reference to the state management table, the departure point of the original plan is changed from the vehicle base (depot) to the current location of the vehicle, the arrival point is maintained at the vehicle base (depot), and job 1 is in state D, so P1 and D1 is excluded, P2 is excluded because job 2 has changed from the state A to C, job 3 is maintained as it is because it is in state A, and P4 and D4 are excluded because job 4 is in state B. As a result, when the original plan is restored, the plan is restored so that the current location, D2, P3, D3, and depot are executed in this order. In this way, by restoring and retaining the original plan, if the current plan obtained by recalculation becomes unavailable due to some problem, it may be immediately available as an alternative plan. Yes and useful.

12 to 14 are explanatory diagrams for explaining the state of determining the optimum route. As shown in FIG. 12A, it is assumed that the execution order of executing the services in the order of delivery destinations A, B, and C from the vehicle base is determined.

FIG. 12B describes a case where the conventional shortest path search process is performed in the situation of FIG. 12A. That is, in the case where only one stop position candidate at each service execution point is adopted and the shortest route is adopted, as shown in FIG. 12B, the arrival direction and the departure direction are as shown in the delivery destination B. If they are different, it will be necessary to make a U-turn on the road. This is a great cost in terms of safety reasons, required time, and mental burden on the driver. In actual work, routes are created so that U-turns do not occur at the visited destination, but the existing solutions for VRP and PDP could not output a solution that suppressed U-turns.

FIG. 13 illustrates an approach method for solving the problems of conventional VRP and PDP. For example, if a route other than a U-turn can be searched, it becomes possible to move from B to C by a detour route as shown in FIG. 13 (a). Alternatively, as shown in FIG. 13B, if the optimum route can be searched by considering a plurality of points as stop position candidates, a U-turn is not made by using the stop position at the delivery destination B as another candidate. It will be possible to move to.

FIG. 14 shows a state in which a plurality of stop position candidates are adopted at each service execution point in order to adopt the above approach. Further, instead of completely prohibiting U-turns, setting a high cost value for U-turns makes it easier for other routes to be adopted as a result. That is, peripheral cost information is set so that the cost value is calculated high for movements in which the arrival direction and the departure direction are different.

The contents of the execution order determination process are as follows. Convert jobs and vehicle states into VRP and PDP inputs. First, the current position of each vehicle or the destination n points ahead in the current plan is set as the departure depot of the vehicle (n is a parameter). Consider the parameter n because there is a need not to break the current destination or the latest plan. The departure time of the depot is defined as the work completion time at n points ahead when it is assumed that the work is completed up to n points ahead. The arrival depot shall be the same as the arrival depot in the plan. Next, consider the state of the job. First, when fixing up to n points, it is assumed that the points have been completed up to n points, and the "state in reality" and the "state in the current plan" are updated respectively. Next, the luggage whose "state in reality" is B or D does not need to be included in the plan, so it is excluded. Since the luggage of C needs to be distributed by the currently loaded vehicle, the allocation of the service of distributing to the vehicle is fixed, and it is set that the vehicle is loaded with the luggage from the beginning. By solving VRP and PDP after making the above settings, it is possible to perform recalculation that takes into account the actual state.

The processing contents in the optimum route determination processing are as follows. First, input the candidate stop position for each visit destination. Then, the shortest route is acquired for each combination of departure direction and arrival direction for any two stop positions between each visit destination. Focusing on a vehicle with a certain solution, it is considered that the route (order of visits) of that vehicle is fixed. The cost of the entire route can be calculated by determining the stop position candidates and the departure / arrival directions for all the visited destinations, and it can be regarded as a combinatorial optimization problem that determines the combination that minimizes the cost. A low-cost route can be obtained by using known methods such as the greedy method and the local search method for this problem. For example, when using the greedy algorithm, first look at the destination from the beginning of the route, and then consider a certain destination i and the previous destination j. Select the departure direction of j, the stop position of i, and the arrival direction of i so that the sum of the cost of the route from j to i and the U-turn cost at j is the smallest. By repeating this until the end of the route, it is expected that a route with a low cost can be obtained. When using the local search method, first, the stop position and departure / arrival direction are randomly determined for all the visited destinations. Next, randomly select a destination, and select the stop position and departure / arrival direction at that point so that the cost is the lowest. By repeating this a certain number of times and for a certain period of time, it is expected that a route with a low cost to some extent can be obtained.

As described above, according to the optimum route determination device according to this example, the service specific information acquisition unit that acquires the service specific information including the execution point information for each of the plurality of services is optimally combined with the execution order of the plurality of services. Execution point-specific information that acquires execution point-specific information including information on at least one stop position candidate at the execution point of each service for each of the execution order determination unit that calculates and determines the execution order as a combinatorial problem. Since the acquisition unit and the optimum route determination unit for determining the optimum route including the information on the optimum stop position and / or the optimum stop direction at each execution point are provided by using the execution order and the information peculiar to the execution point. By considering a plurality of stop position candidates when determining the optimum route, it is possible to determine the optimum route in consideration of the stop position and the stop direction.

Further, a job status management unit for updating the status management table for managing the status of a job configured by at least one related service according to a change in the job status is further provided, and the execution order determination unit is provided. Obtain the job status information by referring to the status management table, identify the service that needs to be executed from the job status information, acquire the service specific information for the specified service, and execute the execution order based on the acquired service specific information. Therefore, when determining the execution order, it is possible to confirm the job status information in the status management table, extract the services that need to be executed, and then determine the execution order. That is, even if the vehicle has already started moving and the plan is being executed, it is possible to acquire the status information of the job at that time and recalculate the execution order.

The present invention is not limited to the above embodiment. Not only home delivery service, but also wholesale business to stores, maintenance of vending machines, home-visit medical care / home-visit care, shared taxi, etc. Applicable to. Moreover, it can be applied to an automatic driving robot even if it is not a vehicle driven by a human. For example, route optimization of AGV (Automated guided vehicle) in the factory, automatic cleaning robot at home, etc., which optimizes the route by taking into account the time when the automatic delivery robot makes a U-turn on the roadside. It can be widely applied. Furthermore, it is also possible to automatically determine the position where the vehicle can stop from the surrounding area from the past results and the characteristics of the road simply by inputting the destination, and to determine the optimum stop position by this algorithm. .. Furthermore, it is also possible to optimize where to enter and where to go from among multiple places to enter and exit the site of the visited place by simply inputting the visited place by the user.

The present invention is not limited to the embodiments described above, and various configurations or embodiments can be taken without departing from the gist of the present invention.

10 Optimal route determination device 11 Job status management unit 12 Service specific information acquisition unit 13 Vehicle position information acquisition unit 14 Execution order determination unit 15 Execution point specific information acquisition unit 16 Optimal route determination unit 17 Storage unit 20 Service executor terminal 30 Headquarters terminal 40 Communication network

Claims (4)

It is an optimum route determination device for determining the optimum route of movement when continuously processing a plurality of services, each of which is executed at a different point.
A service specific information acquisition unit that acquires service specific information including execution point information for each of the plurality of services, and a service specific information acquisition unit.
A job status management unit that updates the status management table for managing the status of jobs configured by at least one related service according to changes in the status of jobs.
It is provided with an execution order determination unit that determines the execution order by combining the execution orders of the plurality of services and calculating as an optimization problem.
The execution order determination unit acquires the status information of the job by referring to the status management table, identifies the service that needs to be executed from the status information of the job, and acquires the service specific information for the identified service. And decide the execution order based on the acquired service specific information,
Further, the execution order determination unit shall calculate a plurality of solutions of the execution order having different predetermined conditions for solving the combinatorial optimization problem, and the predetermined conditions for the adopted execution order are other predetermined conditions. When the condition is changed, the execution order is switched to correspond to the other predetermined conditions, and the execution order is switched based on the status information of the job at that time and the position information of the vehicle at that time. An optimal route determination device that executes recalculation with the initial solution to determine the execution order. The state management table treats the work of delivering the target picked up by the vehicle to a predetermined position as a unit of one job, and as the state of the job, (A) before mounting on the vehicle (planned to be loaded in this plan). (B) Before loading on the vehicle (not planned to be loaded in this plan), (C) Before unloading from the vehicle (planned to be unloaded in this plan), (D) Before unloading from the vehicle (not planned to be unloaded in this plan), (E ) After being unloaded from the vehicle, it has five target states, (F) with the allocation destination vehicle, and (G) without the allocation destination vehicle, and has two plans, and the job status can be determined by combining these. The optimal route determination device according to claim 1 to be managed. When the predetermined recalculation condition is satisfied, the execution order determination unit acquires the status information of the job by referring to the status management table, and is based on the status information of the job different from the plan before the recalculation. The optimum route determination device according to claim 1 or 2, wherein the service that needs to be executed is specified and the execution order is determined for the specified service. It is an optimal route determination program for making a computer realize the process of determining the optimum route of movement when continuously processing a plurality of services executed at different points.
To the computer
A service specific information acquisition function that acquires service specific information including execution point information for each of the plurality of services, and a service specific information acquisition function.
A job status management function that updates the status management table for managing the status of jobs configured with at least one related service according to changes in the status of the job, and
The execution order determination function that determines the execution order by combining the execution orders of the plurality of services and calculating as an optimization problem is realized.
The execution order determination function acquires the status information of the job by referring to the status management table, identifies the service that needs to be executed from the status information of the job, and acquires the service specific information for the identified service. And decide the execution order based on the acquired service specific information,
Further, the execution order determination function shall calculate a plurality of solutions of the execution order having different predetermined conditions when solving the combination optimization problem, and the predetermined condition of the adopted execution order is another predetermined condition. When the condition is changed, the execution order is switched to correspond to the other predetermined conditions, and the execution order is switched based on the status information of the job at that time and the position information of the vehicle at that time. An optimal route determination program that executes recalculation with the initial solution to determine the execution order.

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