Route retrieval device, route retrieval method, and program

Abstract

A route retrieval device according to one aspect of the present invention retrieves routes according to which vehicles are moved to a plurality of bases that provide services to users. The route retrieval device comprises a network information input unit, a status input unit, an order-of-restoration retrieval unit, and an access concentration influence degree calculation unit. The network information input unit inputs network information regarding a network which has a plurality of bases as nodes and links the nodes. The status input unit inputs the status of each of the nodes and links. The order-of-restoration retrieval unit formulates a planning problem for modelling the access concentration of traffic in the network on the basis of the network information and the statuses, and retrieves candidates for the order of restoration of the bases as routes. The access concentration influence degree calculation unit evaluates the influence degree of the access concentration for each of the orders of restoration by using an objective function value obtained by optimizing the planning problem.

Description

Route search device, route search method, and program

[0001] One aspect of the present invention relates to a route search device, a route search method, and a program.

[0002] Delivery services are attracting attention. They not only deliver parcels and other items, but also include the delivery of recovery vehicles after disasters such as earthquakes and typhoons. For example, when a telecommunications company loses power due to a disaster, it immediately dispatches power supply vehicles and workers to buildings that provide telecommunications services (telecommunications buildings). Large-scale power outages during widespread disasters require the delivery of fuel, and equipment failures necessitate equipment replacement. Optimizing delivery routes is important for speeding up the recovery of telecommunications buildings.

[0003] The vehicle routing problem (VRP) is a problem of optimizing the order (restoration order) of multiple vehicles visiting multiple bases. The criteria for evaluating each restoration order are traffic volume and the number of users that can communicate.

[0004] Non-Patent Document 1 discloses a technique for optimizing the restoration order in order to maximize the amount of traffic flowing between specific endpoints when restoring nodes in a network in a step-by-step manner.

[0005] Non-Patent Document 2 discloses a technique for maximizing the traffic volume between specific endpoints up to the upper limit of the capacity in consideration of the routes of a multi-layer network in the event of a large-scale failure.

[0006] J. Wang, et al. "On progressive network recovery after a major disruption," INFOCOM, 2011. K. Genda, et al. "Multi-stage network recovery considering traffic demand after a large-scale failure," ICC, 2016.

[0007] Existing technologies optimize the restoration order of bases by considering only traffic volume, but do not consider communication quality. Furthermore, they do not consider factors such as the number of users connected to the communication service or the number of affected users. In light of this, it has been considered to optimize the restoration order based on the impact, for example, using an index based on the number of users unable to connect to a point of interface (POI). If factors such as access concentration due to a decrease in the number of communication buildings that can communicate could be combined with this, it may be possible to calculate an even more accurate restoration order.

[0008] The present invention has been made in light of the above circumstances, and aims to provide a technique that makes it possible to calculate a restoration order that minimizes the impact on communication services.

[0009] A route search device according to one aspect of the present invention is a route search device that searches for a route for moving a vehicle to multiple bases that provide services to users. The route search device includes a network information input unit, a status input unit, a recovery order search unit, and an access concentration impact calculation unit. The network information input unit inputs network information of a network in which multiple bases are nodes and links connect the nodes. The status input unit inputs the status of each node and link. The recovery order search unit formulates a planning problem that models traffic access concentration in the network based on the network information and the status, and searches for candidate recovery orders for the bases as routes. The access concentration impact calculation unit evaluates the impact of access concentration on each recovery order using an objective function value obtained by optimizing the planning problem.

[0010] According to one aspect of the present invention, it is possible to calculate a restoration order that minimizes the impact on communication services.

[0011] FIG. 1 is a diagram for explaining a use case of an embodiment. FIG. 2 is a diagram for explaining a use case of an embodiment. FIG. 3 is a block diagram showing an example of a route search device according to an embodiment of the present invention. FIG. 4 is a functional block diagram showing an example of the route search device 100 shown in FIG. 3. FIG. 5 is a diagram for explaining the impact of access concentration. FIG. 6 is a diagram showing the flow of data between functional blocks in the processor 10. FIG. 7 is a flowchart showing an example of a processing procedure of the route search device according to the embodiment. FIG. 8 is a diagram for explaining a method for optimizing a recovery order using the impact of access concentration. FIG. 9 is a diagram showing an example of a network topology. FIG. 10 is a diagram showing a route selected by a method using a multi-item flow according to the embodiment. FIG. 11 is a diagram showing a route selected by traffic maximization.

[0012] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to the accompanying drawings. First, a use case of the embodiment will be described with reference to FIGS.

[0013] 1 is a diagram illustrating an example of a use case of a route search device according to an embodiment. For example, when a disaster occurs in which a communication building is damaged, a communication carrier performs recovery measures by having a vehicle 2 visit the damaged communication building 1. Since resources required for recovery work are limited, a plan is made to recover each communication building 1 in stages. In this case, in order to determine the order in which to visit the communication buildings 1, it is necessary to consider the importance of the communication building in terms of communication services.

[0014] By appropriately assessing the importance of communication buildings in a network, it becomes possible to formulate a restoration plan that minimizes the impact on communication services. In order to individually assess the importance of each communication building, in this embodiment, the status of communication services in the restoration state of each communication building is evaluated. In other words, the impact of the failure or restoration of a communication building on communication services is quantitatively evaluated.

[0015] As shown in FIG. 2, by prioritizing the restoration of important communication buildings, the degree of impact can be reduced in stages, and the total degree of impact can be minimized.

[0016] 3 is a block diagram showing an example of a route search device 100 according to an embodiment of the present invention. The route search device 100 in FIG. 3 is a device that searches for a route for moving a vehicle to a plurality of bases that provide services to a user.

[0017] The route search device 100 is a computer including a processor 10, a memory 20, a storage 50, an input / output unit 60, and a bus 45 that connects these components. The input / output unit 60 establishes a communication link between the route search device 100 and the cloud 200, and exchanges various types of data.

[0018] The processor 10 is an arithmetic device such as a CPU (Central Processing Unit) or an MPU (Micro Processing Unit), and realizes processing functions according to the embodiment in accordance with a program loaded from the storage 50 into the memory 20 .

[0019] Fig. 4 is a functional block diagram showing an example of the route search device 100 shown in Fig. 3. In Fig. 4, the memory 20 is a semiconductor memory such as a read only memory (ROM) or a random access memory (RAM).

[0020] The storage 50 is a non-volatile memory such as a hard disk drive (HDD) or a solid state drive (SSD), and stores a program 51 for implementing the processing according to the embodiment in addition to basic software such as an operating system (OS). That is, the program 51 can be installed in the route search device 100.

[0021] The storage 50 also has an area for storing the network topology 52 of the network to be searched for a route, an area for storing the number of users 53, an area for storing location data 54, and an area for storing travel time data 55.

[0022] The network topology 52 is data representing the topology of the network that is the target of the route search. In this embodiment, multiple bases to which the vehicle delivers are referred to as nodes, and the nodes are referred to as links (or arcs).

[0023] The number of users 53 is the number of users at each base (node). In other words, it is the number of users using the network service at each base. The location data 54 is the location of each base, expressed, for example, as latitude and longitude. The travel time data 55 is data that indicates the travel time between each base in matrix format.

[0024] The processor 10 includes a damage status input unit 11, a recovery order search unit 12, a network information input unit 13, and an access concentration impact calculation unit 14 as processing functions according to an embodiment of the present invention.

[0025] The damage situation input unit 11, the recovery order search unit 12, the network information input unit 13, and the access concentration impact calculation unit 14 are realized by the processor 10 executing a program loaded into the memory 20. In other words, the program 51 includes instructions to cause the processor 10 to function as the damage situation input unit 11, as the recovery order search unit 12, as the network information input unit 13, and as the access concentration impact calculation unit 14.

[0026] The network information input unit 13 inputs network information of the network. The network information can be input by, for example, an operator (user). In this case, the network information input unit 13 provides the operator with a GUI (Graphical User Interface) environment. The network information can include, for example, a network topology 52 stored in storage 50, the number of users per location 53, and travel time data 55 between locations. Furthermore, the network information can include link capacity, the number of users at each node, and traffic demand.

[0027] The network information input unit 13 stores the input data in the storage 50. That is, the disaster situation input unit 11 stores the network topology 52, the number of users 53, the location data 54, and the travel time data 55 in the storage 50. For example, the network information input unit 13 passes the location data 54 to a map API (Application Programming Interface) 201 of the cloud 200, acquires the travel time data 55 returned in response, and stores it in the storage 50. The map API 201 is a service provided by the cloud 200.

[0028] The damage status input unit 11 acquires the damage status of the nodes and the damage status of the links, for example, through input by an operator.

[0029] The recovery order search unit 12 formulates a planning problem that models traffic access concentration in the network. The recovery order search unit 12 formulates the planning problem based on, for example, the network information and the disaster situation. Furthermore, the recovery order search unit 12 searches for candidate recovery orders for bases as routes for the vehicle 2 based on the formulated planning problem.

[0030] The access concentration impact calculation unit 14 evaluates the impact of access concentration on each recovery order using the objective function value obtained by optimizing the planning problem. The access concentration impact calculation unit 14 also feeds back the evaluation of the impact of access concentration to the recovery order search unit 12, causing it to search for an optimal solution for the path. The finally obtained optimal solution is the optimal path 300. The input / output unit 60 outputs the calculated optimal path 300.

[0031] 5 is a diagram illustrating the impact of access concentration. In this embodiment, a model is created to quantitatively evaluate the number of users affected by network access concentration in order to evaluate the importance of communication buildings in disaster recovery. Here, the number of users whose communication quality deteriorates due to access concentration in communications from users accommodated in each communication building to a POI is defined as the "impact of access concentration." The impact of access concentration is distinguished from other indicators, such as the "impact of communication interruption."

[0032] Incidentally, the impact of a communication interruption can be calculated using a maximum flow algorithm, which calculates the number of users that can be connected to a POI when the available routes are fully utilized.

[0033] However, when the maximum flow algorithm is applied to the calculation of access concentration, it tends to select a route where access concentration occurs frequently because it maximizes the flow up to the link capacity.In addition, since it does not distinguish between users who use the link, it is not possible to evaluate the impact of access concentration on users.

[0034] As shown in Figure 5, to formulate access concentration, we model the situation where user traffic volume exceeds the link capacity. During a large-scale disaster, the number of available communication routes decreases, and access concentration on a specific link reduces the communication quality for users using that link. Routing control protocols include methods for selecting the shortest route and methods for bypassing access concentration points, so we consider the case where the best route is selected from the perspective of access concentration.

[0035] In this embodiment, the optimal route is determined to minimize the impact, and the number of users affected by communication is calculated based on the access concentration status of the link at that time. For example, the network topology, link capacity, number of users at each node, and traffic demand are input, and the flow on the link is determined by optimizing the planning problem. After counting the number of users affected by access concentration, the impact of access concentration is calculated.

[0036] Here, we will explain the planning problem that models access concentration using mathematical formulas. Here, we consider a multi-item flow to distinguish the flows from each node. The input and output are defined as follows:

[0037] The flow conservation law at each node is expressed by equation (1). The left side of equation (1) is the sum of the flows (i, j) from user h. In the second term of the right side, Src ｉｉ = Src ｉS in i∈S represents a node set, and H in h∈H represents a user set.

[0038] If access concentration is expressed as traffic exceeding the capacity of the link, then <1> and equation (2) hold.

[0039] M in the second part of the right-hand side of equation (2) is a sufficiently large number. (i, j) ∈ E represents a link set.

[0040] If the communication of the node is affected, then the condition is {circumflex over (2)} and the formula (3) holds true: In the formula (3), the product of variables is linearized.

[0041] The condition for minimizing the number of affected users is expressed by equation (4).

[0042] The planning problem formulated as above is optimized, and the impact of access concentration is evaluated using the objective function value at that time.

[0043] 6 is a diagram showing the flow of data between functional blocks in the processor 10. As shown in FIG. 6, the impact of access concentration output from the access concentration impact calculation unit 14 is fed back to the recovery order search unit 12, and calculations are repeated until the recovery order with the smallest impact is found. The finally obtained solution provides a recovery order that minimizes the impact on communication services.

[0044] 7 is a flowchart showing an example of a processing procedure of the route search device 100 according to the embodiment. In FIG. 7, the route search device 100 acquires input network information (step S1). During this process, the route search device 100 also acquires a network topology 52, a number of users 53, position data 54, and travel time data 55. Furthermore, the damage status of each node and link is also acquired.

[0045] Next, the route search device 100 formulates a planning problem that models traffic access concentration in the network based on the acquired network information and the disaster situation (step S2).

[0046] Next, the route search device 100 optimizes the planning problem and searches for candidate base restoration orders as routes (step S3). The route search device 100 then evaluates the impact of access concentration on each restoration order using the objective function value obtained by optimizing the planning problem. The results are fed back until an optimal solution is obtained, and are output from the input / output unit 60 (step S4).

[0047] 8 is a diagram illustrating a method for optimizing the restoration order using the impact of access concentration. In this embodiment, the node to be restored next is determined so as to minimize the impact of access concentration in a network that is in the process of restoration. Nodes A and B in FIG. 8 are considered as candidates for the node to be restored next. In both cases of FIGS. 8(a) and 8(b), all users can connect to the POI, so the impact of communication interruption is 0.

[0048] However, the impact of access concentration varies depending on the link capacity and traffic concentration situation. For example, if the impact in Figure 8(a) is 20 and the impact in Figure 8(b) is 40, node A, which has the smaller impact, will be restored first.

[0049] The difference between route selection using a multi-item flow according to the embodiment and route selection based on traffic maximization will be described with reference to Figures 9 to 11. Taking the network topology shown in Figure 9 as an example, consider communication from the two nodes on the left to the POI on the right in Figures 10 and 11.

[0050] Fig. 10 shows a case where a route is selected to optimize the planning problem of the embodiment and minimize the impact. Fig. 11 shows a case where a route is selected using the maximum flow algorithm and the impact of access concentration is calculated.

[0051] The method for maximizing traffic volume does not consider which link will experience access concentration, so either the solution shown in Figure 10 or Figure 11 can be obtained. The solution shown in Figure 11 results in access concentration on both links, resulting in a decrease in communication quality for both communications (dotted arrows). On the other hand, the solution shown in Figure 10 takes access concentration into account, making it possible to evaluate the impact of selecting a route that minimizes the impact. In other words, selecting a route that minimizes the impact is the same as the idea behind the maximum flow algorithm for the impact of communication interruptions, which maximizes the use of available routes.

[0052] As described above, in the embodiment, network access concentration is formulated as a planning problem, and the impact of access concentration when the route with the least impact is selected is output, taking into account the user traffic volume and the network link capacity. This makes it possible to evaluate the number of users whose communication quality will be reduced due to access concentration when optimizing a vehicle's route. In other words, by taking into account network traffic and the number of users, the number of affected users can be evaluated. Furthermore, by modeling access concentration, the number of users affected by the degradation of communication quality due to access concentration can be evaluated.

[0053] By doing so, it is possible to calculate a recovery order that minimizes the impact on users whose communication quality deteriorates (even though they can connect to the network service) due to concentrated access to the network service. Therefore, it is possible to formulate a recovery plan that minimizes the impact on users whose communication quality deteriorates. From these points, according to the embodiment, it is possible to calculate a recovery order that minimizes the impact on communication services.

[0054] It should be noted that the present invention is not limited to the above-described embodiment. For example, in the embodiment, a configuration has been described in which the route search device 100 includes a damage status input unit 11, a recovery order search unit 12, a network information input unit 13, and an access concentration impact calculation unit 14. Alternatively, it is of course possible to implement these functional blocks in a server computer separate from the route search device 100. In this configuration, the route search device 100 passes the generated planning problem from the input / output unit 60 to the server computer and receives a solution. Alternatively, each functional block may be implemented as a service of the cloud 200.

[0055] That is, this invention is not limited to the above-described embodiments, and the components can be modified and embodied in practice without departing from the spirit of the invention. Furthermore, various inventions can be formed by appropriately combining multiple components disclosed in the above-described embodiments. For example, some components may be omitted from all the components shown in the embodiments. Furthermore, components from different embodiments may be appropriately combined.

[0056] 1...Communication building 2...Vehicle 10...Processor 11...Damage status input unit 12...Recovery order search unit 13...Network information input unit 14...Access concentration impact calculation unit 20...Memory 45...Bus 50...Storage 51...Program 52...Network topology 54...Location data 55...Travel time data 60...Input / output unit 100...Route search device 200...Cloud 300...Optimal route.

Claims

1. A route search device that searches for a route for moving a vehicle to a plurality of bases that provide services to a user, comprising: a network information input unit that inputs network information of a network in which the plurality of bases are nodes and links are between the nodes; a situation input unit that inputs the respective statuses of the nodes and the links; a restoration order search unit that formulates a planning problem that models traffic access concentration in the network based on the network information and the situation, and searches for candidate restoration orders for the bases as the route; and an access concentration impact calculation unit that evaluates the impact of the access concentration on each of the restoration orders using an objective function value obtained by optimizing the planning problem.

2. The route search device according to claim 1, wherein the network information includes a network topology of the network, the number of users at each of the bases, and travel time between each of the bases.

3. The path search device according to claim 1, wherein the restoration order search unit formulates the planning problem using a multi-item flow.

4. The route search device according to claim 1, wherein said restoration order search unit models said access concentration as said traffic exceeding the capacity of said link.

5. A route search method using a computer to search for a route for moving a vehicle to a plurality of bases that provide services to a user, comprising the steps of: the computer acquiring network information of a network in which the plurality of bases are nodes and links exist between the nodes; the computer acquiring the status of each of the nodes and the links; the computer formulating a planning problem that models traffic access concentration in the network based on the network information and the status, and searching for candidate restoration orders for the bases as the route; and the computer evaluating the impact of the access concentration on each of the restoration orders using an objective function value obtained by optimizing the planning problem.

6. A program including instructions for causing a computer to function as a route search device according to any one of claims 1 to 4.