JP6661168B2 - Delivery planning system, delivery planning method and program - Google Patents

Description

  The present invention relates to a delivery planning system, a delivery planning method, and a program.

  The need for car sharing is growing. Car sharing is, for example, a system in which members use a vehicle jointly, pay a fee according to the boarding time, and use the vehicle at their own convenience. As one form of car sharing, there is a use form called a drop-off type (one-way type). In the drop-off type car sharing, the user can use a shared vehicle to a predetermined parking lot near the destination and leave the car in the parking lot as it is. In such a form of car sharing, it is necessary to deliver a vehicle that has been used by a user to another parking lot that has a new use need.

  In addition, in the case of a so-called after-service patrol in which a service technician goes to the customer in order to provide after-sales service for the product purchased by the customer, the same situation exists for the movement of the service technician and parts necessary for providing the service. Occurs. For example, a product that is subject to after-sales service is installed at each of a plurality of customers, and a serviceman procures parts to be used for after-sales service of the product at a certain location and transports it to the customer, or in one round of patrol Servicemen who provide various types of after-sales services are efficient when moving from one customer who needs the same parts to provide another service to another customer, and then returning the used parts to the original place. It becomes necessary to select a patrol method.

  Patent Document 1 discloses a technique for creating a transportation plan for transporting a package from a plurality of delivery points to a plurality of delivery destinations at a specified date and time by using a plurality of transportation means.

JP 2013-136421 A

By the way, even in the case of delivery of vehicles in car sharing, if the method is such that vehicles are loaded on trucks and delivered, there is a possibility that the technology of Patent Document 1 or the like can be applied. However, when delivering vehicles by car sharing, there is also a method in which a delivery staff gets on a vehicle to be delivered and drives to a target parking lot. Such a method of boarding and delivering the goods to be delivered is called boarding transportation. 2. Description of the Related Art Conventionally, for a delivery method in which packages are loaded on a vehicle and delivered, a method of optimizing a delivery route based on a mathematical model has been provided. However, there is no technology provided for performing an optimal delivery plan in delivery including boarding transport.
Similarly, when parts to be used for service are to be delivered to the customer in the after-sales service patrol, if only parts are delivered from the service center to each customer, a patrol plan can be made by a conventional method, but the serviceman When moving with a part, delivering parts from one customer to another, or leaving a surplus part with a serviceman for the next customer, it is the same as boarding transport However, there is no technology provided for optimal tour planning by service personnel.

In general, a combinational optimization problem of discrete values generally uses a method called linear relaxation, that is, a method in which a problem is once replaced with a continuous value problem and solved to obtain an optimal solution from the obtained relaxation solution. If there are many complicated constraints such as a problem, the calculation time will be too long without any change, and a device for solving the problem in a practical time is required.

  Accordingly, an object of the present invention is to provide a delivery planning system, a delivery planning method, and a program capable of solving the above-described problems, and to shorten the calculation time.

  According to the first aspect of the present invention, the delivery planning system includes a delivery plan for each delivery base, which is a place where any of a delivery, a delivery entity, the delivery, or a delivery unit that moves the delivery entity remains. Demand quantity and supply quantity, information on one or more departure bases indicating the initial position of the delivery entity and the delivery means, information on available delivery means and delivery entities at the departure base, and information on delivery deadlines And an initial condition setting unit for setting initial conditions in a delivery plan, point information in which the delivery base and the departure base and a time based on delivery start are set, and Calculate the branch information indicating the flow rate of the delivery item and the delivery subject and the delivery means between the two pieces of point information related to the delivery of the delivery item, and calculate the demand quantity within the delivery deadline. The delivery article satisfying comprising a delivery plan generator, for generating at least one set of the branch information when delivered to the delivery site where the demand quantity is set.

  The delivery plan generation unit according to the second aspect of the present invention may calculate an evaluation value for the generated set of branch information, and determine an optimal set of branch information based on the evaluation value.

  The delivery plan generation unit according to a third aspect of the present invention includes: branch information indicating the flow rate between different delivery bases; and branch information indicating the flow rate in the same delivery base and the departure base. May be generated.

  The delivery plan generation unit according to a fourth aspect of the present invention, for one of the delivery bases, sets point information relating to an entrance paired with the entrance and the time of the delivery base, and the exit and the time of the delivery base. Point information relating to the paired exits and point information relating to a place where the delivery is grouped with respect to time for each one of the deliverables relating to the delivery base are generated, and the point information relating to the entrance and the delivery are provided. The values of the flow rate of the delivery subject and the delivery between the point information about the article and the point information about the exit and the point information about the delivery may be set to 0 or 1.

  The delivery plan generation unit according to a fifth aspect of the present invention sets the delivery entity, the delivery means, and an objective function that minimizes a cost based on a flow rate and a travel time of the delivery, and sets the delivery, delivery For each of the means and the delivery entity, the difference between the flow rate entering the delivery base and the flow rate exiting the delivery base is zero, and the flow rate of the delivery, the flow rate of the delivery means, and the flow rate of the delivery entity are each zero or more. That each of the flow rate of the delivery item in the delivery base and the flow rate of the delivery entity is 1 or less, and when the flow rate of the delivery item in the delivery base is 1, the flow rate of the delivery item is The flow rate of the delivery subject is 1, that the delivery means always board the delivery means when moving from the delivery location to another delivery location, and from the delivery location to the other delivery location. The number of the delivery entities boarding the delivery means when moving is less than or equal to the number of boardable people, and the total of the delivery items and delivery means loaded on the delivery means when moving from the delivery base to another delivery base. Is less than or equal to the amount that can be loaded on the delivery means related to the movement, if the delivery subject stays in the delivery base, the delivery entity rides on the delivery means, and if the delivery subject stays in the delivery base, board the delivery means The set of branch information may be determined by solving an integer programming problem that includes, as a constraint, that the number of deliveries is equal to or less than the number of boardable people.

  In the sixth aspect of the present invention, the delivery plan generation unit sets an objective function that minimizes a travel time of the delivery subject, the delivery unit, and the delivery, instead of the objective function that minimizes the cost. , The set of branch information may be determined by solving the integer programming problem.

  The delivery plan generation unit according to a seventh aspect of the present invention may determine a set of the branch information by adding a constraint condition regarding the delivery means that goes out of the delivery base that supplies the delivery.

  The delivery plan generation unit according to an eighth aspect of the present invention may determine a set of the branch information by adding a constraint condition regarding the delivery means entering the delivery base where the demand for the delivery is required.

  The delivery plan generation unit according to a ninth aspect of the present invention adds a constraint condition relating to a relationship between an increase or decrease of the delivery items in a place where the delivery items are stored in the delivery base and a number of the delivery entities entering the place. The set of the branch information may be determined by the above.

  The delivery plan generation unit according to a tenth aspect of the present invention may determine a set of the branch information by adding a constraint on an increase or decrease of the delivery in a place where the delivery is stored in the delivery base. .

  The delivery plan generation unit according to an eleventh aspect of the present invention further includes, when there are a plurality of places for the deliverables in the delivery base, adding a constraint condition regarding an order of adding and taking out the deliverables to a plurality of places, and A set of branch information may be determined.

  The delivery plan generation unit according to a twelfth aspect of the present invention may determine the set of the branch information by adding a constraint on the number of the delivery means.

  According to a thirteenth aspect of the present invention, the delivery can be carried by the delivery entity on board, and the branch information calculated by the delivery plan generation unit includes the branch information by the delivery unit. In addition to the branch information indicating the movement of the delivery, branch information indicating that the delivery main body rides on the delivery and moves the delivery may be included.

  According to a fourteenth aspect of the present invention, in the delivery planning method, the delivery planning device is provided for each delivery base where any one of a delivery, a delivery entity, the delivery, or a delivery unit that moves the delivery entity remains. Demand quantity and supply quantity of the delivery, information of one or more departure bases indicating the delivery entity and the initial position of the delivery means, information of available delivery means and delivery entity at the departure base, Receiving the input of information on the delivery deadline, setting initial conditions in the delivery plan, and setting the delivery base and the departure base and time based on delivery start as point information; Calculate the branch information indicating the flow rate of the delivery item and the delivery subject and the delivery means between the two pieces of point information related to the delivery of the delivery item, and calculate the demand quantity within the delivery deadline. Plus delivery was generating at least one set of the branch information when delivered to the delivery site where the demand quantity is set.

  According to a fifteenth aspect of the present invention, the program causes the computer of the delivery planning device to include, for each delivery base that is a place where any one of a delivery, a delivery entity, the delivery, or delivery means for moving the delivery entity remains. Demand quantity and supply quantity of the delivery, information of one or more departure bases indicating the delivery entity and the initial position of the delivery means, information of available delivery means and delivery entity at the departure base, Means for receiving input of information on a delivery deadline and setting initial conditions in a delivery plan, point information in which the delivery base and the departure base are paired with a time based on delivery start, Among the two pieces of point information related to the delivery of the delivery, the delivery information related to the delivery, the delivery entity, and branch information indicating the flow rate of the delivery means are calculated, and the delivery time limit is set. At least one generated means a set of the branch information when delivering delivery items satisfying the demand quantity delivery locations to which the demand quantity is set, to function as a.

  ADVANTAGE OF THE INVENTION According to this invention, when a delivery staff picks up the delivery thing which exists in various places, and delivers it to an appropriate delivery destination, the delivery plan which minimizes cost and travel time can be made.

It is a functional block diagram showing an example of a delivery planning system in a first embodiment of the present invention. It is a figure explaining an example of a delivery plan in a first embodiment of the present invention. It is an example of the spatiotemporal network model concerning the delivery plan in the first embodiment of the present invention. It is a flow chart which shows an example of generation processing of a delivery plan in a first embodiment of the present invention. It is a functional block diagram showing an example of a delivery planning system in a second embodiment of the present invention. FIG. 11 is a first diagram illustrating a spatiotemporal network model according to a delivery plan according to the second embodiment of the present invention. FIG. 11 is a second diagram illustrating a spatiotemporal network model according to a delivery plan in the second embodiment of the present invention. It is the 3rd figure explaining the spatiotemporal network model concerning the delivery plan in a second embodiment of the present invention. It is the 4th figure explaining the spatiotemporal network model concerning the delivery plan in a second embodiment of the present invention. It is the 5th figure explaining the spatiotemporal network model concerning the delivery plan in a second embodiment of the present invention. It is a first figure explaining an example of a cut in a second embodiment of the present invention. It is a 2nd figure explaining an example of a cut in a second embodiment of the present invention. It is the 3rd figure explaining an example of a cut in a second embodiment of the present invention. It is the 4th figure explaining an example of a cut in a second embodiment of the present invention. It is the 5th figure explaining an example of a cut in a second embodiment of the present invention. It is a 6th figure explaining an example of a cut in a second embodiment of the present invention. It is the 7th figure explaining an example of a cut in a second embodiment of the present invention. It is an eighth figure explaining an example of a cut in a second embodiment of the present invention. It is a ninth figure explaining an example of a cut in a second embodiment of the present invention. It is a tenth figure explaining an example of a cut in a second embodiment of the present invention. It is an eleventh figure explaining an example of a cut in a second embodiment of the present invention. It is a twelfth figure explaining an example of a cut in a second embodiment of the present invention. It is a figure explaining an example of a restriction in a second embodiment of the present invention. It is a figure showing an example of a problem of a delivery plan in a second embodiment of the present invention. FIG. 13 is a first diagram illustrating an example of a result of planning a delivery plan according to the second embodiment of the present invention. It is a second figure showing an example of the result of planning of the delivery plan in a second embodiment of the present invention.

<First embodiment>
Hereinafter, a delivery planning system according to an embodiment of the present invention will be described with reference to FIGS.
FIG. 1 is a functional block diagram illustrating an example of a delivery planning system according to the first embodiment of the present invention. In the present embodiment, the delivery planning system includes, for example, one computer device such as a PC or a server device. The computer device includes an arithmetic unit such as a CPU (Central Processing Unit), a storage unit such as a ROM (Read Only Memory), a RAM (Random Access Memory), and an HDD (Hard Disk Drive), and other hardware such as a network interface. It is configured to include hardware.

  The delivery planning device 10 in FIG. 1 is an example of a delivery planning system. The delivery planning device 10 is a device that calculates a delivery method, a delivery route, and the like that minimize costs for a delivery plan that includes boarding transportation. In the present embodiment, in a case where a vehicle shared by users is delivered to a place where the user starts to use in a drop-off type car sharing, a method of drafting an optimal delivery plan for realizing the delivery will be described as an example. When delivering a delivery, for example, it is required to select a delivery means and a delivery route that minimize costs. Various methods have been provided for designing a delivery plan that minimizes costs. However, delivery of vehicles in car sharing differs from, for example, delivery of luggage by home delivery or the like. That is, when a vehicle is delivered, a person can travel on the vehicle. For example, it is assumed that there is a surplus or a shortage of vehicles at each of the bases A, B, C, D, and E. In such a state, for example, the following method can be considered in order to move the vehicle from the surplus base to the shortage base so as to meet the needs of the user. (1) One delivery staff goes around each base by a truck capable of loading a vehicle, mounts the surplus vehicle on the truck, and delivers it to a base having a shortage. (2) A plurality of delivery staffs board the delivery vehicle and move to each base. When the delivery staff on board the delivery vehicle arrives at the base where there is surplus vehicles, transfer to a surplus vehicle and drive the vehicle to the base where there is a shortage of vehicles to deliver (boarding transport). In such a case, it is not easy to know which delivery means should be used for delivery and which route should be used to minimize the cost. The delivery planning device 10 of the present embodiment quickly and efficiently minimizes costs, for example, by introducing a mathematical model and constraints based on mathematical knowledge into a delivery plan when boarding transport is possible. Provides a way to determine a delivery plan.

As shown in FIG. 1, the delivery planning device 10 includes an initial condition setting unit 11, a delivery plan generation unit 12, an input / output unit 13, and a storage unit 14.
The initial condition setting unit 11 is provided with a delivery item for each delivery base that is a place where any of the delivery items that the delivery entity can board and move, the delivery entity, the delivery items, or the delivery means that moves the delivery entity stays. Such as the demand quantity and supply quantity, information on one or more departure bases indicating the delivery entity and the initial position of the delivery means, information on available delivery means and delivery entities at the departure base, and information on the delivery deadline. Information is set as initial conditions for calculating a delivery plan. These parameters will be described later in detail.
The delivery plan generation unit 12 is configured to transmit the point information, which is a set of the delivery base and the departure base, and the time based on the start of the delivery, and the delivery item related to the delivery between the two pieces of the point information related to the delivery. Calculate branch information indicating the flow rate of the delivery entity and the delivery means, and generate at least one set of branch information in the case of delivering a delivery that satisfies a demand quantity within a delivery deadline to a delivery base where the demand quantity is set. . Departure bases and delivery bases are collectively called bases.
The input / output unit 13 receives an input operation by a user. In addition, the input / output unit 13 outputs information on a delivery plan based on a set of branch information generated by the delivery plan generation unit 12 to a display or the like.
The storage unit 14 stores various information necessary for generating a delivery plan.
The delivery plan generation unit 12 is realized by, for example, reading and executing a program from the storage unit 14 by a CPU (Central Processing Unit) provided in the delivery planning device 10.

FIG. 2 is a diagram illustrating an example of a delivery plan according to the first embodiment of the present invention.
An example of delivery of a delivery (vehicle) in a drop-off type car sharing will be described with reference to FIG. In FIG. 2, the center is a base where the delivery staff of the delivery exists and starts delivery of the delivery (departure base). Further, the parking lot A, the parking lot B, and the parking lot C are bases (delivery bases) which are delivery sources or destinations of the delivery. The user of the delivery makes a reservation for the delivery using a predetermined reservation system or the like. The user inputs information such as the number of used deliveries and the use start location (for example, parking lot B) from the reservation system. When the user wants to use the delivery from parking lot B, if the delivery already exists in parking lot B, the user can use the delivery. However, when there is no delivery in parking lot B, the delivery staff needs to move the delivery from another parking lot to parking lot B. In the drop-off type car sharing, for example, when a user uses a delivery from the parking lot B to the parking lot A, the user drops the delivery to the parking lot A as it is. Then, a situation may occur in which many users use, for example, a delivery is ubiquitous in the parking lot A. The delivery staff at the center delivers the ubiquitous deliveries to the parking lots A to C where the user needs. In the case of the example of FIG. 2, two or more deliveries are missing in the parking lot A, and one or more deliveries are insufficient in the parking lots B and C. The delivery staff at the center delivers the remaining two deliveries in the parking lot A to the parking lot B and the parking lot C, respectively, so that the user can use the deliveries as desired. FIG. 2 shows an example of a delivery that satisfies this condition.

  First, two delivery staffs (k, l) from the center board one delivery vehicle 1 (delivery means) and move to the parking lot A (1). In the parking lot A, the delivery staff k moves to the parking lot B by boarding one of the surplus vehicles. Further, the other delivery staff 1 also board the delivery car 1 and moves to the parking lot B (2). In the parking lot B, the delivery staff k parks the delivery in the parking lot B, and gets on the delivery vehicle 1 driven by the delivery staff l. The delivery staffs k and l return from the parking lot B to the parking lot A (3). When returning to the parking lot A, the delivery staff k moves to the parking lot C by boarding one surplus delivery. In addition, the delivery staff 1 boards the delivery vehicle 1 and moves to the parking lot C (4). In the parking lot C, the delivery staff k parks the deliveries in the parking lot C and board the delivery car 1 driven by the delivery staff l. The delivery staffs k and l return from the parking lot B to the parking lot A (5). When the delivery is performed in such a procedure, the request of the user can be satisfied. In the present embodiment, the delivery method of the delivery in such a situation is formulated as the minimum cost flow problem of the spatiotemporal network model, and a method that minimizes the cost among the feasible delivery methods is obtained.

FIG. 3 is an example of a spatio-temporal network model according to the delivery plan in the first embodiment of the present invention.
FIG. 3 is a diagram in which the embodiment of the delivery described in FIG. 2 is modeled in a spatiotemporal network. The vertical axis in FIG. 3 indicates the passage of time, and the horizontal axis indicates the location of each base. In the figure, the points on the spatiotemporal space represent each base at each time. In the figure, an arrow connecting two points indicates a movement in time and space of a delivery, a delivery vehicle (delivery means), and a delivery staff (person). Each arrow indicates a source base, a destination base, and the time required for movement. Solid arrows indicate movement between locations, and double-line arrows indicate deliveries, delivery vehicles, and delivery staff who stay at the same location (moving time). In addition, each element of the matrix displayed along with each arrow represents the number of items, delivery vehicles, and delivery staff moved by the delivery indicated by the arrow. Shows the number of delivery vehicles and the number of delivery staff who have moved. For example, in the case of the solid line arrow 31, it indicates that there are 0 vehicles, one delivery vehicle, and two delivery staff members have moved from the center to the parking lot A between time t = 0 and t = 1. I have. Further, the double-line arrow 32 indicates that, in the parking lot A, there are two deliveries, zero deliveries, zero delivery staff, and stayed from time t = 0 to t = 1. . Further, in the case of the solid arrow 33, it is assumed that one delivery item, one delivery vehicle, two delivery staff members have moved from the parking lot A to the parking lot B between the time t = 1 and t = 2. Is shown. Further, the double line arrow 34 indicates that, in the parking lot A, one delivery item, zero delivery vehicles, zero delivery staff, and stayed during the time t = 1 to t = 2. . The number of deliveries in the parking lot A changed from two to one because the delivery staff boarded one of the two deliveries and moved to the parking lot B. The same applies to other arrows. In addition, one arrow is called a branch. The set of branches in FIG. 3 corresponds to the delivery plan described in FIG. When delivering a delivery, there may be a time-related action such as waiting for a delivery staff or delivery means at some parking lot. Existing mathematical models related to delivery planning often model locations as points and movement of delivery vehicles between the locations as branches. In the present embodiment, modeling is performed using a two-dimensional next space network. Thus, not only the spatial movement between the bases but also the movement of a vehicle or a person whose time intervenes can be represented.

In the present embodiment, a delivery plan that minimizes the cost required for delivery in a delivery plan delivery that satisfies demand within the time limit as described with reference to FIGS. This problem can be formulated as the following integer programming problem.
[Objective function]
Minimize the total cost of delivery items, delivery means, and delivery staff required for delivery [Constraints]
(1) The flow rate at each site satisfies the flow rate conservation law.
(2) The number of vehicles existing in the parking lot does not exceed the parking space of the parking lot.
(3) A delivery staff always rides on the delivery means except at the departure point.
(4) When moving, the delivery staff always rides on the delivery or the delivery means, and the number of people at the time of movement is equal to or less than the total number of people who can board the delivery and the delivery means.

  In order to solve the integer programming problem, the delivery plan generation unit 12 generates a branch between points related to delivery as illustrated in FIG. 3 based on the information on the initial conditions received by the initial condition setting unit 11. Then, a plurality of sets of branch information that can deliver the delivery to the base where the demand quantity is set are generated so as to satisfy the demand quantity of each base within the delivery deadline. Then, the delivery plan generation unit 12 selects a set of branch information that minimizes cost from a set of a plurality of branch information. Note that more specific contents of the objective function and the constraint condition will be described in a second embodiment.

FIG. 4 is an example of a flowchart of a delivery plan generation process in the first embodiment of the present invention.
First, a delivery staff who performs a delivery plan inputs initial conditions of a delivery plan to the delivery planning device 10. The input / output unit 13 receives the input and outputs the received information to the initial condition setting unit 11. The initial condition setting unit 11 acquires information on the initial condition input by the delivery staff (step S11). The initial condition setting unit 11 sets the acquired information of the initial condition as the initial condition of the delivery plan. The initial conditions include, for example, the supply quantity (remaining quantity), the demand quantity (insufficient quantity), the number of delivery vehicles at the departure base, the number of delivery staff, and the number of delivery staff at each base. For example, travel time and delivery deadline.
Next, the delivery plan generation unit 12 generates branch information on the spatiotemporal network model illustrated in FIG. 3 so as to satisfy the above-described constraint condition, and performs delivery such that the demand number of each base is satisfied by the delivery deadline. Are generated (Step S12).
Next, the delivery plan generation unit 12 calculates a cost for each set of generated branch information (step S13). For example, the unit cost generated per unit time for each delivery vehicle, delivery staff, and delivery item is recorded in the storage unit 14 in advance, and the delivery plan generation unit 12 stores the unit cost of the delivery vehicle, delivery staff, and delivery item in the storage unit 14. Multiply the time indicated by each branch to calculate the cost for each branch (total cost for delivery vehicles, delivery staff, and delivery). The delivery plan generation unit 12 calculates the cost for each branch included in the set of branch information and totals them. The total cost is the cost for one set of branch information. The delivery plan generation unit 12 calculates a cost for each set of all pieces of branch information.
Next, the delivery plan generation unit 12 compares the calculated costs for each of the calculated sets, and selects a set of branch information with the minimum cost (step S14). The set of the selected branch information represents the movement of the delivery item, the delivery means, and the delivery staff over time from the state of the departure base and each delivery base indicated by the initial condition (FIG. 3). Therefore, if the delivery is executed based on the set of the branch information, the delivery according to the demand from the user can be performed. That is, this set of branch information is the delivery plan to be obtained.

  The mathematical models and programs of delivery plans that have existed so far are limited to the case where a delivery is loaded and delivered to a transportation means such as a truck or a railroad. For vehicles that include boarding transport, such as vehicle delivery, existing technologies may be able to be solved by adding constraints, but the constraints are complicated and the number of combinations of means and routes is limited. It is considered impractical due to the exponential increase. According to the present embodiment, when calculating a delivery plan of a delivery that can be boarded and transported, the cost is minimized among the feasible delivery methods by formulating it as a minimum cost flow problem of the spatiotemporal network model. A delivery plan can be requested.

<Second embodiment>
Hereinafter, a delivery planning system according to a second embodiment of the present invention will be described with reference to FIGS.
In the second embodiment, a graph (point information and delivery staff, delivery information, and branch information indicating the movement of delivery means) in a delivery base is further added to the spatiotemporal network model of the first embodiment. As a result, the inside of the delivery base can be treated as a 0-1 integer planning problem. Since the variable width of the 0-1 integer programming problem is more limited than that of the integer programming problem, the number of combinations is reduced, and the calculation time can be shortened. Further, in the second embodiment, a cut is added to further speed up the calculation. In the second embodiment, more efficient cut insertion is possible by subdividing the movement within the delivery base.

FIG. 5 is a functional block diagram illustrating an example of a delivery planning system according to the second embodiment of the present invention.
In the configuration according to the second embodiment of the present invention, the same components as those constituting the delivery planning device 10 according to the first embodiment of the present invention are denoted by the same reference numerals, and description thereof will be omitted.
The delivery plan device 10a according to the second embodiment includes a delivery plan generation unit 12a instead of the delivery plan generation unit 12 in the configuration of the first embodiment.
The delivery plan generation unit 12a combines the point information that pairs the entrance and the time of the delivery base and the exit and the time of the delivery base for one delivery base, in addition to the function of the delivery plan generation unit 12. Point information, point information in which time is set for each of the items to be delivered related to the delivery base is generated, and the delivery staff and the flow rate of the delivered item between the point information related to the entrance and the point information related to the delivered item. Is set to 0 or 1. In addition, the delivery plan generation unit 12a sets the value of the delivery staff and the flow rate of the delivery between the point information on the exit and the point information on the delivery to 0 or 1.

Here, the parameters that the delivery planner inputs to the delivery planning device 10a will be described. The input parameters include the following items.
That is, a set of departure bases (Depot), a set of delivery bases (W), a delivery deadline (dl), a time of one section (h), a set of delivery types (P), a set of delivery vehicle types (D) ), Loading amount of delivery means (cp), delivery cost cx (yen / min), delivery car cost cy (yen / min), delivery staff cost cz (yen / min), travel time matrix M (for example, The travel time from the delivery point w1 to the delivery point w2 by the delivery means d is m [d] [w1] [w2]), and the supply quantity “supply” at each point (for example, the supply quantity d at the delivery point w is “supply [w]”). , D]), and the demand quantity demand of each delivery base (for example, the demand quantity of d at the delivery base w is demand [w, d]). The initial condition setting unit 11 acquires these parameters and sets them as initial conditions of the delivery plan.

  Further, as output items, the delivery plan generation unit 12a outputs the flow rate x ((v, s), (w, t)) of the delivery item flowing through the spatiotemporal network in the optimized delivery plan, and the flow rate y ( (V, s), (w, t)) and the flow rate z ((v, s), (w, t)) of the delivery staff are output to the input / output unit 13. Note that a branch that departs from the delivery base v at time s and arrives at the delivery base w at time t is represented by ((v, s), (w, t)). The output items include other costs for delivery.

FIG. 6 is a first diagram illustrating a spatiotemporal network model according to a delivery plan according to the second embodiment of the present invention.
The spatiotemporal network used in the second embodiment will be described with reference to FIG. Hereinafter, it is assumed that a place set is N, a time set is T, and a graph of a spatiotemporal network is G = (V, E). V is a point set and E is a branch set. The point set V is defined as follows.
V = {(w, d, p, t) | w} W, d {0} P, p {S _wd , t} T}
Here, S _wd = {0, 1} (d = 0), S _wd = {0, 1,. . . , M｝ (d ≠ 0). d = 0 indicates the road at the entrance of the delivery base. When d = 0, S _wd takes a value of 0 or 1, where S _wd = 0 indicates an entrance and S _wd = 1 indicates an exit. In addition, in the case of d ≠ 0, d indicates the type of delivery _{products, S wd} takes the value of 0~m. m is the supply quantity -1 or the demand quantity -1 for the delivery d at the delivery base w. For example, when three delivery items a are left at the delivery base w (supply quantity = 3), S _wd takes a value of 0, 1, or 2. Further, for example, when four delivery items a are insufficient at the delivery base w (demand quantity = 4), S _wd takes a value of 0, 1, 2, or 3. Note that, for a certain delivery base w, a point at d = 0 is also called a road, and a point at d ≠ 0 is also called a port. The port indicates a place where one delivery item d is placed.

FIG. 6 shows that Depot = {0}, W = {1,2}, P = {a}, T = {0,1,2}, _S1a = {0} (supply for delivery a at delivery base 1) This is a spatiotemporal network in the case of _S2a = {0} (one demand quantity for delivery a at delivery base 2). Next, the branch set E will be described with reference to FIG.

FIG. 7 is a second diagram illustrating a spatiotemporal network model according to a delivery plan according to the second embodiment of the present invention.
Hereinafter, the edge set E, and _{E = E x ∪E y ∪E z} . Branch set of E _x the delivery product, E _y branches set of delivery means, E _z is a branch set of delivery staff.
Branch set E _x of delivery was defined as follows.
_{E x = E wwx ∪E wx ∪E} wpx ∪E pwx ∪E px
E _wwx is a set of branches indicating the movement of the delivery between bases, E _wx is a set of branches (such as waiting) that stay on the road of the delivery base of the delivery, and E _wpx is the movement of the delivery from the road to the port. set of _branches, E pwx is a set of branches that show the movement of the road from the port of delivery products, E _px is a set of branches delivery product remains in port.

Branch set E _y of the delivery means are defined as follows.
E _y = E _wwy ∪E _wy ∪E _wpy ∪E _pwy
E wwy shows a set of branches showing the movement between the base of the delivery means, the set of E _wy branches that remain in the way of delivery base of the delivery means (such as waiting), the movement of the _E wpy is to port from the way of the delivery means A set of branches, _Epwy, is a set of branches indicating movement from the port of the delivery means to the road.

Branch set E _z of delivery staff are defined as follows.
E _z = E _wwz ∪E _wz ∪E _wpz ∪E _pwz
E _wwz is a set of branches indicating the movement of the delivery staff between bases, E _wz is a set of branches (meeting, etc.) staying on the way of the delivery base of the delivery staff, and E _wpz indicates movement from the way of the delivery staff to the port. A set of branches, E _pwz, is a set of branches indicating the movement of the delivery staff from the port to the road.

FIG. 7 shows a display example of the branch set defined above. The solid arrow in the oblique direction indicates the branch corresponding to each set of _{Ewwx, Ewwy, and Ewwz} . Vertical double-line arrows indicate branches corresponding to each set of E _wx, E _{wy, and} E _wz . The two-dot chain arrow in the horizontal direction indicates a branch corresponding to each set of E _wpx, E _{wpy, and} E _wpz . The dashed-dotted arrow in the oblique direction indicates a branch corresponding to each set of _{Epwx, Epwy, and Epwz} . The vertical dashed arrows indicate branches corresponding to the set of _Epx .
In the present embodiment, the inside of the delivery base is treated as a 0-1 integer problem, but branches of a horizontal two-dot chain arrow, a diagonal one-dot chain arrow, and a vertical broken arrow are related to the 0-1 integer problem. Thus, the branch added in the present embodiment.

FIG. 8 is a third diagram illustrating a spatiotemporal network model according to a delivery plan according to the second embodiment of the present invention.
The flow vector set for each branch will be described with reference to FIG. As shown in FIG. 8A, each branch e has a flow rate vector.

Is set. Of this flow vector, x [d, e] ( d∈P, e∈E x) is the flow rate of delivery items, y [d, e] ( d∈D, e∈E y) is the delivery vehicle flow, z [e] (e∈E _z ) indicates the flow rate of the delivery staff. Here are some examples. In the case of P = {a} and D = {car}, the flow vector is

Becomes The branch e shown in FIG. 8B shows the movement of one a, one delivery vehicle, and two delivery staff (people). When P = {a, b} and D = {car, motorcycle}, the flow rate vector is

Becomes A branch e shown in FIG. 8C shows the movement of one a, one b, one delivery vehicle, one motorcycle, and two delivery staff (people).

FIG. 9 is a fourth diagram illustrating a spatiotemporal network model according to a delivery plan in the second embodiment of the present invention.
FIG. 9 shows that the flow vector is

This is a spatio-temporal network model when one delivery item a is moved from the delivery site 1 to the delivery site 2. First, two delivery staffs and one delivery vehicle move from the Depot exit to the delivery base 1 (solid arrow 91). At the delivery site 1, one delivery staff moves to the place (port 0) where the delivery item a is stored (two-dot chain line arrow 92). At port 0 of the delivery a, the delivery a exists from time 0 to time 1 (broken arrow 93). Subsequently, one delivery staff and one delivery item a1 move to the exit of the delivery base 1 (the dashed-dotted arrow 94). Next, one delivery item a, one delivery vehicle, and two delivery staff members move from the exit of the delivery base 1 to the entrance of the delivery base 2 (solid arrow 95). Next, one delivery staff member and one delivery item a move to port 0 of delivery base 2 (two-dot chain arrow 96). Subsequently, one delivery staff moves from the port 0 to the exit of the delivery base 2 (the one-dot chain line arrow 97). Next, two delivery staff and one delivery vehicle move from the exit of the delivery base 2 to the Depot entrance (solid arrow 98). At port 0 of the delivery base 2, the delivery item a exists from time 2 to time 3 (dashed arrow 100). As shown in FIG. 9, in the present embodiment, at the delivery base 1 and the delivery base 2, a point is assigned to each delivery item a, and a point is assigned to each of the entrance and the exit of the delivery base. Therefore, the value of each element of the flow vector in the delivery base 1 and the delivery base 2 is 0 or 1. As a result, the inside of the delivery base can be treated as a 0-1 integer programming problem, and the calculation time can be shortened.

FIG. 10 is a fifth diagram illustrating a spatiotemporal network model according to a delivery plan in the second embodiment of the present invention.
FIG. 10 is a spatiotemporal network model representing the spatiotemporal network model illustrated in FIG. 3 of the first embodiment by the method of the second embodiment. In the present embodiment, the point set represented by the column of the parking lot A in FIG. 3 is further subdivided into (1, 0, 0, 0), (1, a, 0, 0), (1, a, 1). , 0). The same applies to the parking lot B and the parking lot C. Further, a point set corresponding to the entrance is given to each of the center and the parking lots A to C.

  Next, a cut for further shortening the calculation time will be described. In the integer programming problem, an inequality that can be satisfied by a point in the feasible region is called a valid inequality. Since integer programming problems are difficult to solve, they are often treated as linear relaxation problems excluding integer conditions. Adding a valid inequality that reduces the solution space of a linear relaxation problem is called adding a cut. The addition of the cut brings the linear relaxation solution closer to the integer optimal solution, which has a strong effect on speeding up the calculation. Also, the addition of the cut does not cut the feasible region, so the optimality of the solution is guaranteed.

FIG. 11 is a first diagram illustrating an example of a cut according to the second embodiment of the present invention.
FIG. 11 is a diagram illustrating a cut related to the number of delivery vehicles that go out of a road where a supply is provided.
E ₁ is a set of branches entering the road, E ₂ shows a set of branches leaving the road. The following equation (A) is established from the constraint conditions 5 and 6 described later.

Equation (A) is a cut for the number of delivery vehicles leaving the road with supplies. Note that the right side of the equation (A) indicates that a value obtained by dividing α by β−1 is rounded up to the nearest decimal point. The same applies to the following expressions.
Here, α represents the maximum number of rideable passengers in all the deliveries. β represents the maximum number of occupants in all delivery vehicles.

FIG. 12 is a second diagram illustrating an example of a cut according to the second embodiment of the present invention.
FIG. 12 is a diagram illustrating a cut related to the number of delivery vehicles entering a road with a demand.
E ₁ is a set of branches entering the road, E ₂ shows a set of branches leaving the road. The following Expression (B) is established from the constraint conditions 5 and 6 described later.

Equation (B) is a cut related to the number of delivery vehicles entering the road where the demand is.
Here, α represents the maximum number of rideable passengers in all the deliveries. β represents the maximum number of occupants in all delivery vehicles.

FIG. 13 is a third diagram illustrating an example of a cut in the second embodiment of the present invention.
FIG. 13 is a diagram for explaining cuts related to the number of delivery vehicles that go out from a road with supplies to time t. To appear before time t means to appear before time t-1.
E ₁ is a set of branches by the time t enters the road, E ₂ is a set of branches leaving the road by the time t, E ₃ shows a set of vertical branch of the port leaving at a time t. The following equation (C) is established from the constraint conditions 5 and 6 described later.

  Equation (C) is a cut for the number of delivery vehicles leaving the road with supplies by time t.

FIG. 14 is a fourth diagram illustrating an example of a cut in the second embodiment of the present invention.
FIG. 14 is a diagram illustrating a cut related to the number of delivery vehicles that go out of a road with a demand after time t.
E ₁ is a set of branches by the time t enters the road, E ₂ is a set of branches leaving the road by the time t, E ₃ shows a set of vertical branch of the port to enter at a time t. The following equation (D) is established from the constraint conditions 5 and 6 described later.

  Equation (D) is a cut related to the number of delivery vehicles that go out from the road with the demand to the time t.

FIG. 15 is a fifth diagram illustrating an example of a cut according to the second embodiment of the present invention.
FIG. 15 is a diagram illustrating a cut obtained by expanding the cut described in FIGS. 11 and 13.
E ₁ is a set of branches leaving the road by the time t, E ₂ is a set of branches by the time t enters the road, E ₃ shows a set of vertical branch of the port leaving at a time t. e ₄ shows a set of branches of the vertical of the road entering in the time t. The following inequality (cut) (E) is derived by the mathematical operation of the constraint equation similar to that described with reference to FIGS. For a road with supply quantity a,

  Holds.

FIG. 16 is a sixth diagram illustrating an example of a cut in the second embodiment of the present invention.
FIG. 16 is a diagram illustrating a cut obtained by expanding the cut described in FIGS. 12 and 14.
E ₁ is a set of branches after the time t enters the road, E ₂ is a set of branches leaving the road in time t, E ₃ shows a set of vertical branch of the port to enter at a time t. e ₄ shows a set of branches of the vertical of the way out in time t. The following inequality (cut) (F) is derived by the mathematical operation of the constraint equation similar to that described with reference to FIGS. For a road with supply quantity a,

  Holds.

FIG. 17 is a seventh diagram illustrating an example of a cut in the second embodiment of the present invention.
FIG. 18 is an eighth diagram illustrating an example of a cut in the second embodiment of the present invention.
The cut acting between the road and the port will be described with reference to FIGS.
x (e) indicates the number of deliveries on the branch e, and z (e) indicates the number of persons on the branch e. FIG. 18 is a table summarizing the relationship among z (e ₁ ), x (e ₂ ), x (e ₃ ), and x (e ₄ ). For example, if the delivery staff does not enter the port from the road, there is no change in the number of deliveries at the port. Also, if the delivery staff enters the port from the road, the number of deliveries at the port always changes. For example, if x (e ₂ ) is 1, it means that the user went out with a delivery. Further, for example, if x (e ₄ ) is 1, it indicates that a delivery has been brought. The following equation is obtained from the table of FIG.
z (e ₁ ) −x (e ₂ ) + x (e ₃ ) −x (e ₄ ) = 0
This formula is the cut that works between the road and the port. By adding this cut, there is no need to calculate when the delivery staff enters and exits the port in a meaningless manner.

  In addition, a monotonically increasing cut can be added to a port having demand. The monotonically increasing cut specifies that the number of deliveries only increases from 0 to 1 at a port with demand, and does not return to 0 again after increasing from 0 to 1.

  Also, a monotonically decreasing cut can be added to the port where the supply is. The monotonically decreasing cut specifies that the number of deliveries only decreases from 1 to 0 at the port where the supply is provided, and does not increase from 1 to 0 and then to 1 again. .

  Further, it is possible to add a cut for determining the order of satisfying the request at the port having demand. Specifically, a condition is added that a branch from a road to a port having demand is brought in ascending port number.

  Further, it is possible to add a cut that determines the order in which the request is satisfied at a certain supply port. More specifically, a condition is added that branches from a given port to a road are taken in ascending port number.

FIG. 19 is a ninth diagram illustrating an example of a cut in the second embodiment of the present invention.
FIG. 20 is a tenth diagram illustrating an example of a cut in the second embodiment of the present invention.
The cut of the number of delivery vehicles will be described with reference to FIGS.
E ₁ is a set of branches in the time t enters the road, e ₂ branches coming from the road at time t to the port, e ₃ shows the branches entering the road from the port to the customer at the time t-1. FIG. 19 is a table summarizing the relationship among z (e ₁ ), z (e ₂ ), and y (E ₁ ). y (E) indicates the total number of delivery vehicles of each branch of the branch set E, and z (e) indicates the number of persons on the branch e. The following equation is obtained from the table of FIG.
z (e ₁ ) ≦ z (e ₂ ) + y (E ₁ )
This formula is the cut of the number of delivery vehicles.

FIG. 21 is an eleventh diagram illustrating an example of a cut in the second embodiment of the present invention.
FIG. 21 shows an example of the result when the linear relaxation problem is solved without cutting the number of delivery vehicles described in FIGS. If the cut of the number of delivery vehicles is not applied as shown in the figure, there is a possibility that 3/4 delivery vehicles will come. However, in reality, more than one delivery vehicle should come.

FIG. 22 is a twelfth diagram illustrating an example of a cut in the second embodiment of the present invention.
FIG. 22 shows an example of the result when the linear relaxation problem is solved by adding the cut of the number of delivery vehicles described in FIGS. As shown in the figure, when the number of delivery vehicles is cut, one or more delivery vehicles must come. FIGS. 21 and 22 show that by adding a cut, an unrealistic case where the number of deliverers comes in 3/4 can be excluded from the calculation target.

  By adding a cut in this way, the range of the solution is limited, and the calculation is speeded up. Specifically, it became possible to solve an integer programming problem that took several hours or more without adding a cut to solve the problem in a few minutes when adding a cut including the one exemplified above .

  As described above, the measures for increasing the processing speed in the second embodiment have been described in which the inside of the delivery base is set to the 0-1 integer planning problem and the addition of the cut. Next, the objective function and the constraint of the integer programming problem will be described more specifically from the first embodiment. In addition, as a delivery means, a description will be given of a case of delivery by a delivery vehicle and a bicycle (including a case of delivery by a delivery vehicle alone) and a case of delivery by a truck. In addition, the bicycle of the delivery means, the delivery staff rides the bicycle and moves to the delivery base where the supply is provided, where the surplus vehicles are loaded with bicycles, and the delivery staff drives the surplus vehicle and moves to the delivery base where there is demand To be used.

First, the objective function will be described. In the first embodiment, the case where the cost is minimized has been described as an example. In the present embodiment, a description will be given including a case where the traveling time required for delivery is minimized.
(When delivering by delivery car and bicycle)
1. The objective function for minimizing the cost of delivery is the sum of the cost per hour for each of the delivery, delivery vehicle, and delivery staff multiplied by the travel time.
2. The objective function for minimizing the travel time required for delivery is the sum of the travel times of the delivery, delivery vehicle, and delivery staff.

(When delivering by truck)
1. The objective function for minimizing the cost of delivery is the sum of the cost per hour of the delivery truck and delivery staff multiplied by the travel time.
2. The objective function for minimizing the travel time required for delivery is the sum of the travel times of the delivery truck and delivery staff.

Next, the restrictions will be described.
(Common to delivery by delivery car and bicycle and delivery by truck)
1. Flow Conservation Law (1) Regarding Flow Rate of Delivered Items At the start of delivery, the flow rate flowing out of the port where the supply is present is 1. At the point of completion of the delivery, the flow rate entering the port where the demand exists is 1. Otherwise, the outgoing and incoming flows are equal.

(2) Flow rate of delivery vehicles At the start of delivery, the flow rate of the vehicles on the road where the delivery vehicles exist is equal to the number of delivery vehicles. At the time of completion of the delivery, the flow rate on the road where the delivery vehicle exists is equal to the number of delivery vehicles. Otherwise, the outgoing and incoming flows are equal.
(3) Flow rate of delivery staff At the start of delivery, the flow rate of the delivery staff on the road is equal to the number of delivery staff. At the time of completion of the delivery, the flow rate on the road where the delivery staff exists is equal to the number of delivery staff. Otherwise, the outgoing and incoming flows are equal.
2. The amount of movement of the goods and persons within the capacity-constrained delivery base is 1 or less.

3. Restrictions in delivery base 1
∀e∈E _wp (FIG. 23 illustrates E _wp )
(1) When the destination of e is the supply point of d The delivery does not enter the port from the road.
(2) When the destination of e is the demand point of d The flow rate of the delivery and the delivery staff take the same value (0 or 1).
(3) In both cases, the number of bicycles is less than the number of delivery staff.

4. Restrictions in delivery base 2
∀e∈E _pw (FIG. 23 illustrates E _pw )
(1) When the starting point of e is the supply point of d The flow rate of the delivery and the delivery staff take the same value (0 or 1).
(2) When the starting point of e is the demand point of d The delivery does not leave the port from the port.
(3) In both cases, the number of bicycles is less than the number of delivery staff.

Hereinafter, a case where delivery is performed by a delivery car and a bicycle and a case where delivery is performed by a truck will be described separately.
(When delivering by delivery car and bicycle)
5. Restriction on branch when moving from base to another base {e} E _ww
(1) When e is a branch of a bicycle and a branch of a car There are cases where the delivery staff is moving on each of the bicycle and the car, and cases where the bicycle is loaded on the car and moving. The delivery staff must be on board, the number of delivery staff must be less than the number of boardable people, and the number of bicycles that cannot be driven must be less than the number that can be loaded on the car.
(2) When e is a bicycle branch but not a car branch (moving by bicycle)
The number of bicycles and the number of people match.

6. Restrictions on Branches Remaining in Delivery Bases Cars must be occupied by people, and the number of people must be less than the maximum number of passengers.

(When delivering by truck)
5. Restrictions on branches when moving from one delivery base to another delivery base Always have a delivery staff on the truck, the number of delivery staff must be less than the number of boardable people, and the total volume of deliveries should be less than the loading capacity of the truck. There is a constraint.

6. Restrictions on Branches Remaining in the Base The delivery staff must be less than the maximum number of passengers, and the total volume of deliveries must be less than the load capacity of the truck.

  In step S12 of FIG. 4, the delivery plan generation unit 12a generates a spatiotemporal network model in which the inside of the delivery base is divided by a road (d = 0) and a parking port (d ≠ 0). The branch information is calculated using the added cut. According to the present embodiment, since the inside of a delivery base can be modeled as a 0-1 integer planning problem, the effect of reducing the time required for calculating the delivery plan can be obtained in addition to the effect of the first embodiment. . Further, the calculation time can be significantly reduced by adding a cut. As a result, for example, the delivery plan calculated under various initial conditions can be compared, and a lower-cost delivery plan can be selected, thereby improving the convenience of the planner.

Next, a case where the delivery plan is calculated by the delivery plan device 10a of the present embodiment will be described.
FIG. 24 is a diagram illustrating a problem example of a delivery plan according to the second embodiment of the present invention.
Point 0 (depot) in FIG. 24 is a departure point. Other points 1 to 9 are delivery bases. For example, “d1: 2” at point 7 indicates a state in which two delivery items d1 are left, and “d2: −1” at point 5 indicates that one delivery item d2 is short. It shows the state where it is. Further, "d1: -1, d2: 1" at point 2 indicates a state in which one delivery d1 is short and one delivery d2 is left. Consider a problem in which the delivery items d1 to d3 are delivered from the state where the delivery items d1 to d3 shown in FIG. An example of a delivery plan calculated by the delivery planning device 10a for the case of delivery by car and bicycle and the case of delivery by truck will be described below.

1. Delivery by car and bicycle (1) Input ・ Depot, one delivery car, three bicycles, three delivery staff ・ Delivery time: 120 minutes ・ Delivery car cost: 1.5 yen / minute ・ Delivery staff Cost: 17 yen / min. · Cost of d1, d2, d3: 1.5 yen / min. · Number of passengers in a delivery vehicle: 4, Number of bicycles: 1 · Number of passengers in d1: 1 , Number of bicycles that can be loaded: 0 · Number of people who can ride on d2: 4 people, Number of bicycles that can be loaded: 1 device · Number of people who can ride on d3: 2 People, number of bicycles that can be loaded: 0

(2) Objective function Cost minimization (3) One output / delivery vehicle, one bicycle, and two delivery staff deliver as shown in FIG.
-Delivery cost: 2768 yen-Required time: 60 minutes As described above, a delivery plan that minimizes costs within the conditions of the delivery means, delivery staff, and delivery deadline set in the initial conditions was obtained.

FIG. 25 is a first diagram illustrating an example of a result of planning a delivery plan according to the second embodiment of the present invention.
FIG. 25 shows a delivery plan of delivery vehicles d1 to d3 that minimizes cost. According to the delivery plan calculated by the delivery planning device 10a, delivery is performed by dividing into two routes, a delivery route 1 shown by S1 to S7 and a delivery route 2 shown by T1 to T9. The delivery staff in charge of the delivery route 1 moves and performs delivery in the order of S1 to S7. The delivery staff in charge of the delivery route 2 moves in the order of T1 to T9 and performs delivery. Note that the delivery staff of the delivery route 1 and the delivery staff of the delivery route 2 meet at the delivery base 7 and move from the delivery base 7 to the delivery base 2 together. Although not shown in FIG. 25, for example, for S1, the flow rate x ((depot, departure time), (delivery base 3, arrival time)) of the delivery item = 0, and the flow rate y of the delivery vehicle ((Depot, departure time), (delivery base 3, arrival time)) = 1, and delivery staff flow rate z ((depot, departure time), (delivery base 3, arrival time)) = 2 are output as output items. You. Using this information, the delivery plan can be represented by a spatiotemporal network model illustrated in FIGS.

2. Delivery by truck (1) Input / depot, one truck, 2 delivery staffs / Delivery deadline: 120 minutes / Cost of truck: 25 yen / min. / Cost of delivery staff: 17 yen / min. Loading capacity: 16
・ The volume of d1 is 2, the volume of d2 is 4, and the volume of d3 is 3.

(2) Objective function Cost minimization (3) Output / one truck and one delivery staff deliver as shown in FIG.
-Delivery cost: 3456 yen-Required time: 80 minutes

FIG. 26 is a second diagram illustrating an example of a result of planning a delivery plan according to the second embodiment of the present invention.
FIG. 26 shows a delivery plan of the delivery items d1 to d3 that minimizes the cost. In the case of the delivery plan of FIG. 26 calculated by the delivery planning device 10a, delivery is performed by the delivery routes indicated by 1 to 9. As in FIG. 25, the output items include departure and arrival time information relating to the movement of each delivery base, delivery items, delivery vehicles, and flow rates of delivery staff.

  As illustrated in FIGS. 24 to 26, according to the present embodiment, a delivery plan that minimizes the cost for each of the case where a boardable delivery is delivered by a delivery car and a bicycle and the case of delivery by a truck is provided. Can be calculated. Also, the planner of the delivery plan compares the delivery plans calculated by setting various initial conditions, and examines what delivery means should be used and how many delivery staffs should perform delivery. be able to. Although an example of the delivery cost minimization has been described, as described above, a delivery plan that minimizes the delivery time can be calculated by using the objective function to minimize the travel time required for delivery. Further, in the above example, there is only one departure base, but it is also possible to calculate a delivery plan when there are a plurality of departure bases. Although the second embodiment is more preferable in terms of the time required for the calculation, for example, the problems dealt with in FIGS. 24 to 26 can be solved by the delivery planning device 10 of the first embodiment.

  The process of each process in the delivery planning devices 10 and 10a described above is stored in a computer-readable recording medium in the form of a program, and the computer of the delivery planning system reads out and executes the program to execute the process. Processing is performed. Here, the computer-readable recording medium refers to a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, a semiconductor memory, or the like. Alternatively, the computer program may be distributed to a computer via a communication line, and the computer that has received the distribution may execute the program.

Further, the program may be for realizing a part of the functions described above. Furthermore, what can implement | achieve the function mentioned above in combination with the program already recorded on the computer system, what is called a difference file (difference program) may be sufficient.
Further, the delivery planning devices 10 and 10a may be configured by a single computer, or may be configured by a plurality of computers communicably connected.

  In addition, it is possible to appropriately replace the components in the above-described embodiment with known components without departing from the spirit of the present invention. The technical scope of the present invention is not limited to the above embodiment, and various changes can be made without departing from the spirit of the present invention. For example, the present invention can be applied to delivery, procurement, and after-service patrol of deliveries that can be carried on board. In addition, the present invention can be used for delivery of a delivery that is not carried on board.

For example, in the after-sales service, it is necessary to procure parts and the like necessary for the after-sales service and then go to the customer or provide the service by going to a plurality of customers. Products used for after-sales service, such as parts that use deliveries, and delivery vehicles that are used for transporting vehicles and parts that are used by the serviceman for transportation and serviceman for transportation, and products whose bases are customers and for after-sales service. When the above mathematical model is applied as an installation location, the integer programming problem can be solved by the method described in the first embodiment to the second embodiment, and when a service person performs after-sales service at a plurality of customers, In addition, it is possible to calculate a traveling method (a traveling means, a traveling route) that minimizes the traveling cost and the traveling time. Taking FIG. 2 as an example, parking lots A to C (delivery bases) are customer sites that provide after-sales services, vehicles (delivery items) are parts, passenger cars (delivery means) are used by servicemen for transportation, The delivery person (delivery subject) may be a service person. In the case of after-sales service, not only patrol the customer, but also work such as inspection and repair at the customer. According to the delivery planning devices 10 and 10a using the spatio-temporal network model, it is possible to model the patrol behavior of the serviceman in consideration of these work times.

The cost for delivery and the travel time for delivery are examples of evaluation values. A delivery staff is an example of a delivery entity, a delivery car, a truck, and a bicycle are examples of delivery means, and a shared vehicle in car sharing is an example of a delivery.

10, 10a: delivery planning device 11: initial condition setting unit 12, 12a: delivery plan generation unit 13, input / output unit 14, storage unit

Claims (15)

A demand quantity and a supply quantity of the deliverables for each delivery base, which is a place where any of the deliverables, the delivery entity, the deliveries or the delivery means moving the delivery entity, and an initial value of the delivery entity and the delivery means Initial information for receiving information on one or more departure bases indicating positions, information on available delivery means and delivery entities at the departure base, and information on delivery deadlines, and setting initial conditions in a delivery plan A condition setting section,
The delivery according to the delivery between point information in which the delivery base and the departure base are combined with a time based on delivery start, and two pieces of point information of the point information related to delivery of the delivery item. The branch information indicating the flow rate of the goods and the delivery subject and the delivery means, and the delivery information satisfying the demand quantity within the delivery deadline is delivered to the delivery base where the demand quantity is set. A delivery plan generation unit that generates at least one set;
A delivery planning system comprising: The delivery plan generation unit calculates an evaluation value for the generated set of branch information, and determines an optimal set of branch information based on the evaluation value.
The delivery planning system according to claim 1. The said delivery plan production | generation part produces | generates the branch information which shows the said flow between different said delivery bases, and the branch information which shows the said flow in the same said delivery base and the said departure base. 2. The delivery planning system according to 2. The delivery plan generation unit, for one of the delivery bases, point information pertaining to an entrance pairing the entrance and time of the delivery base, and point information pertaining to an exit pairing the exit and time of the delivery base. And point information relating to a place for storing the delivery items, each of which has a time set for each of the delivery items relating to the delivery base, and generating the point information relating to the entrance and the point information relating to the delivery item. Setting a value of the flow rate of the delivery subject and the delivery between 0 and 1 between the point information related to the exit and the point information related to the delivery,
The delivery planning system according to any one of claims 1 to 3. The delivery plan generation unit,
Setting an objective function that minimizes the cost based on the flow rate and travel time of the delivery subject and the delivery means and the delivery,
For each of the delivery, the delivery means, and the delivery entity, the difference between the flow rate entering and leaving the delivery base is 0,
Each of the flow rate of the delivery, the flow rate of the delivery means, and the flow rate of the delivery entity is 0 or more;
Each of the flow rate of the delivery item in the delivery base and the flow rate of the delivery subject is 1 or less,
When the flow rate of the delivery in the delivery base is 1, the flow rate of the delivery subject related to the flow rate of the delivery is 1;
The delivery subject always boarding the delivery means when moving from the delivery base to another delivery base,
The number of the delivery entities boarding the delivery means when moving from the delivery site to another delivery site is equal to or less than the number of boardable people.
When moving from the delivery base to another delivery base, the total of the delivery items and the delivery means loaded on the delivery means is equal to or less than the amount that can be loaded on the delivery means related to the movement. The delivery entity rides on the delivery means,
When staying in the delivery base, the number of the delivery entities boarding the delivery means is not more than the number of boardable people,
Solving the integer programming problem containing the constraint conditions to determine a set of the branch information,
The delivery planning system according to claim 4. The delivery plan generation unit,
In place of the objective function that minimizes the cost, an objective function that minimizes the travel time of the delivery entity and the delivery means and the delivery is set,
Solving the integer programming problem to determine the set of branch information;
The delivery planning system according to claim 5. The delivery plan generation unit,
Determining a set of the branch information by adding a constraint condition regarding the delivery means exiting from the delivery base that supplies the delivery item;
The delivery planning system according to claim 5. The delivery plan generation unit,
Determining a set of the branch information by adding a constraint condition regarding the delivery means that enters the delivery base where the demand for the delivery is required;
The delivery planning system according to any one of claims 5 to 7. The delivery plan generation unit,
Determining a set of the branch information by adding a constraint on the relationship between the increase / decrease of the deliverables in the storage area of the deliverables in the delivery base and the number of delivery entities entering the storage area,
The delivery planning system according to any one of claims 5 to 8. The delivery plan generation unit,
Determining a set of the branch information by adding a constraint condition on an increase or decrease of the delivery items in a place where the delivery items are stored in the delivery base;
The delivery planning system according to any one of claims 5 to 9. The delivery plan generation unit,
In the case where there are a plurality of places for the delivery items in the delivery base, the set of branch information is determined by adding a constraint on the order of addition and removal of the delivery items to a plurality of places,
The delivery planning system according to any one of claims 5 to 10. The delivery plan generation unit,
Determining a set of the branch information by adding a constraint on the number of the delivery means entering the delivery base;
The delivery planning system according to any one of claims 5 to 11. The delivery, the delivery subject can move on board,
The branch information calculated by the delivery plan generation unit includes, in addition to branch information indicating the movement of the delivery by the delivery means, a branch indicating that the delivery entity moves on the delivery and moves the delivery. Information is included,
The delivery planning system according to any one of claims 1 to 12. The delivery planning device
A demand quantity and a supply quantity of the deliverables for each delivery base, which is a place where any of the deliverables, the delivery entity, the deliveries or the delivery means moving the delivery entity, and an initial value of the delivery entity and the delivery means Information of one or more departure bases indicating a position, information on available delivery means and delivery entities at the departure base, and input of information on a delivery deadline are received, and initial conditions in a delivery plan are set,
The delivery according to the delivery between point information in which the delivery base and the departure base are combined with a time based on delivery start, and two pieces of point information of the point information related to delivery of the delivery item. The branch information indicating the flow rate of the goods and the delivery subject and the delivery means, and the delivery information satisfying the demand quantity within the delivery deadline is delivered to the delivery base where the demand quantity is set. Generate at least one set,
Delivery planning method. The computer of the delivery planning device,
A demand quantity and a supply quantity of the deliverables for each delivery base, which is a place where any of the deliverables, the delivery entity, the deliveries or the delivery means moving the delivery entity, and an initial value of the delivery entity and the delivery means Means for receiving input of information on one or more departure bases indicating positions, information on available delivery means and delivery entities at the departure base, and information on delivery deadlines, and setting initial conditions in a delivery plan ,
The delivery according to the delivery between point information in which the delivery base and the departure base are combined with a time based on delivery start, and two pieces of point information of the point information related to delivery of the delivery item. The branch information indicating the flow rate of the goods and the delivery subject and the delivery means, and the delivery information satisfying the demand quantity within the delivery deadline is delivered to the delivery base where the demand quantity is set. Means for generating at least one set;
Program to function as

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