Delivery capacity calculation device, delivery capacity calculation method, and program

Abstract

To support efficient delivery.SOLUTION: A delivery reserve capacity calculation device according to one embodiment comprises: an input unit which inputs a delivery object data set constituted by delivery object data expressing a delivery object being a delivery target and a delivery resource data set constituted by delivery resource data expressing a delivery resource delivering the delivery object; a first allocation unit which calculates a first allocation result indicating an allocation result of the delivery resource to each delivery object by solving a delivery plan problem on the basis of each delivery object data constituting the delivery object data set and each delivery resource data constituting the delivery resource data set; a second allocation unit which calculates a second allocation result indicating the allocation result of the delivery resource to one or more virtual delivery objects by repeatedly solving the delivery plan problem on the basis of each of one or more pieces of virtual delivery object data expressing one or more virtual delivery objects and the first allocation result; and a reserve capacity calculation unit which calculates a delivery reserve capacity expressing a reserve capacity of the delivery object that can be delivered by the delivery resource on the basis of the second allocation result.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a delivery margin calculation device. , distribution The present invention relates to a method and a program for calculating a transmission margin. [Background technology]

[0002] When creating a delivery plan, finite delivery resources (e.g., delivery vehicles, delivery personnel, etc.) are generally assigned to deliveries with determined delivery destinations, delivery time slots, etc. For example, delivery resources are assigned to deliveries by solving a vehicle routing problem (VRP) that has constraints such as the delivery time slots of the deliveries, the available operating hours of the delivery resources, and the maximum load that the delivery resources can deliver. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2009-286502 A [Patent Document 2] JP 2015-103246 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the past, there were cases where inefficient deliveries were made. For example, there were cases where a delivery resource heading to a delivery area during a certain time period had to start delivery in order to meet the delivery time slot, even though there was a margin of loading capacity for the delivery resource. On the other hand, if it were possible to know how much loading capacity there is for the delivery resource heading to each delivery area during each time period (hereinafter, this is also referred to as "delivery capacity margin"), it would be possible to take various measures to increase delivery efficiency (for example, if there is delivery capacity margin in a delivery area during a certain time period, then soliciting deliveries to be delivered to that delivery area during that time period at a low price, etc.).

[0005] An embodiment of the present invention has been made in consideration of the above points, and has an object to support efficient delivery. [Means for solving the problem]

[0006] In order to achieve the above-mentioned object, a delivery margin calculation device according to one embodiment includes an input unit for inputting a delivery item data set composed of delivery item data representing items to be delivered and a delivery resource data set composed of delivery resource data representing delivery resources for delivering the items; a first allocation unit for calculating a first allocation result indicating a result of allocation of delivery resources to each delivery item by solving a delivery plan problem based on each delivery item data constituting the delivery item data set and each delivery resource data constituting the delivery resource data set; a second allocation unit for calculating a second allocation result indicating a result of allocation of delivery resources to each of one or more virtual delivery items by iteratively solving the delivery plan problem based on each of one or more virtual delivery item data representing one or more virtual delivery items respectively and the first allocation result; and a margin calculation unit for calculating a delivery margin indicating a margin of delivery items that can be delivered by delivery resources based on the second allocation result. Effect of the Invention

[0007] It can assist in efficient delivery. [Brief description of the drawings]

[0008] [Figure 1] FIG. 2 is a diagram illustrating an example of a hardware configuration of a delivery margin calculation device according to the present embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of a functional configuration of a delivery margin calculation device according to the present embodiment. [Diagram 3] 13 is a flowchart illustrating an example of a delivery margin calculation process according to the present embodiment. [Figure 4] FIG. 13 is a diagram for explaining an example of application to dynamic pricing. [Diagram 5] 13 is a flowchart showing an example of a delivery margin calculation process according to a modified example. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] An embodiment of the present invention will be described below. In this embodiment, a delivery capacity calculation device 10 capable of calculating the delivery capacity for each time period and each delivery area will be described. Calculating the delivery capacity using the delivery capacity calculation device 10 according to this embodiment makes it possible to dynamically set delivery charges according to the delivery capacity, as will be described in an application example below, and to realize efficient delivery. As described above, the delivery capacity is the delivery volume that a delivery resource heading to a delivery area in a certain time period can deliver (typically, the load that can be carried when the delivery resource is a vehicle).

[0010] In this embodiment, the term "delivery" refers to transporting something to a destination, but for example, the term "transportation" may be used instead of "delivery." Also, a delivery item is some item to be delivered, and a delivery resource is a vehicle such as a truck, but these are merely examples, and for example, a delivery item may be a person, animal, plant, etc., and a delivery resource may be a person.

[0011] Here, it is assumed that the delivery margin calculation device 10 according to this embodiment is provided with three data sets (also called data sets) shown in (1) to (3) below.

[0012] (1) Delivery data set A delivery data set is a set of zero or more pieces of delivery data. Delivery data is data that represents various information related to a specific delivery that is an actual delivery target (for example, the collection location of the delivery, the delivery destination of the delivery, and the delivery time period indicating the designated time period during which the delivery will arrive at the destination). In other words, each piece of delivery data included in a delivery data set is data that represents various information related to a delivery that has actually been accepted for delivery (or a delivery that is scheduled for delivery). Note that a case in which the number of delivery data included in a delivery data set is zero refers to, for example, an initial state in which an actual delivery has not yet been accepted for delivery (typically, a state in which no delivery order has been placed).

[0013] In the following, each delivery data set includes the collection location, delivery destination, and delivery time zone of a specific delivery. In other words, the nth delivery data set included in the delivery data set is P n Then, the delivery data set is {P n} n∈N ,P n =(p 1n ,p 2n ,p 3n ), where N is the set of indexes (orders) of deliveries, p 1n is the collection location of the nth delivery, p 2n is the delivery destination of the nth shipment, p 3n represents the delivery time slot of the nth delivery. Hereinafter, the nth delivery will also be referred to as "delivery item n". If no delivery time slot is specified, the delivery time slot p 3n For example, a null value (NULL value) is set to .

[0014] However, this is only an example, and the delivery data may include various information. For example, if various deliveries are the target of delivery, rather than a specific delivery, the delivery data may include the type of delivery. Furthermore, the delivery data may include the amount of the delivery (for example, the size and weight of the delivery), and may include information such as whether refrigerated or frozen delivery is required.

[0015] (2) Delivery resource data set A delivery resource data set is a set of one or more delivery resource data. Delivery resource data is information that represents various information related to delivery resources (for example, the upper limit load capacity indicating the upper limit of the load capacity that a delivery resource can deliver, the available operation time of a delivery resource, and the entry / exit location indicating the departure and return location of a delivery resource).

[0016] In the following, each delivery resource data set includes the upper limit load capacity, available operation time, and storage location of a certain delivery resource. In other words, the m-th delivery resource data set included in the delivery resource data set is denoted as V m Then, the delivery resource data set is {V m} m∈M ,V m =(v 1m ,v 2m ,v 3m ), where M is the set of delivery resource indices, v 1m is the upper limit of the m-th delivery resource, v 2m is the available time of the mth delivery resource, v 3m represents the entry / exit location of the m-th delivery resource. Hereinafter, the m-th delivery resource will also be referred to as "delivery resource m." In this embodiment, the upper limit loading capacity is the upper limit number of deliveries that can be loaded, but it may also be, for example, the upper limit weight or the upper limit size.

[0017] However, this is merely an example, and the delivery resource data may include various information. For example, the delivery resource data may include information on whether refrigerated or frozen delivery is possible.

[0018] (3) Virtual delivery data set A virtual delivery data set is a set of one or more virtual delivery data. Virtual delivery data is data that represents various information related to a specific delivery that is a virtual delivery target, and includes information similar to delivery data. In other words, each virtual delivery data included in the virtual delivery data set is data that represents various information related to a virtual delivery that was created in advance.

[0019] In the following, the kth virtual delivery data in the virtual delivery data set is Q k Then, the virtual delivery data set is {Q k} k∈K ,Q k =(q 1k ,q 2k ,q 3k ) where K is a set of virtual delivery indexes, q 1k is the kth virtual delivery location, q 2k is the destination of the kth virtual delivery, q 3k represents the delivery time slot of the kth virtual delivery item. Hereinafter, the kth virtual delivery item will also be referred to as "virtual delivery item k". If no delivery time slot is specified, delivery time slot q 3k For example, a null value (NULL value) is set to .

[0020] Each virtual delivery data is created in advance by any method. For example, the creation method may be random or according to a certain probability distribution. For example, a set of values ​​that can be taken as a collection location is S 1 Let S be the set of possible delivery destinations. 2 Let S be the set of possible delivery time slots. 3 As, S 1 ,S 2 and S 3 From each of q 1k ,q 2k and q 3kIt is possible to generate K pieces of virtual delivery data by sampling K times randomly or according to a certain probability distribution. In addition, for example, if there are empirical rules or business knowledge regarding delivery areas, delivery time periods, etc., all or part of the virtual delivery data may be manually generated based on the empirical rules or business knowledge.

[0021] The number of virtual delivery data K is set to a sufficiently large value (e.g., |S 1 |×|S 2 |×|S 3 | degree), but as described later, the larger K is, the more times the delivery planning problem must be solved, and the longer it takes to calculate the delivery capacity. Therefore, for example, when creating virtual delivery data by the above sampling, it is recommended to set S 1 ,S 2 ,S 3 After removing some values ​​from q 1k ,q 2k and q 3k Specifically, if there is an empirical rule that a certain delivery area usually runs out of delivery capacity at a certain time, the value representing that delivery area as the delivery destination is set as S 2 and set the value representing the time period as the delivery time period S 3 It may be removed from.

[0022] <Hardware configuration of delivery margin calculation device 10> The hardware configuration of a delivery capacity calculation device 10 according to this embodiment is shown in Fig. 1. As shown in Fig. 1, the delivery capacity calculation device 10 according to this embodiment is realized by the hardware configuration of a general computer or computer system, and has an input device 11, a display device 12, an external I / F 13, a communication I / F 14, a processor 15, and a memory device 16. Each of these pieces of hardware are connected to each other via a bus 17 so as to be able to communicate with each other.

[0023] The input device 11 is, for example, a keyboard, a mouse, a touch panel, various physical buttons, etc. The display device 12 is, for example, a display, a display panel, etc. Note that the delivery capacity calculation device 10 does not necessarily have to have at least one of the input device 11 and the display device 12, for example.

[0024] The external I / F 13 is an interface with an external device such as a recording medium 13a. The delivery capacity calculation device 10 can read and write data from and to the recording medium 13a via the external I / F 13. Examples of the recording medium 13a include a CD (Compact Disc), a DVD (Digital Versatile Disk), a SD memory card (Secure Digital memory card), and a USB (Universal Serial Bus) memory card.

[0025] The communication I / F 14 is an interface for connecting the delivery margin calculation device 10 to a communication network. The processor 15 is, for example, various arithmetic devices such as a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit). The memory device 16 is, for example, various storage devices such as a HDD (Hard Disk Drive), an SSD (Solid State Drive), a flash memory, a RAM (Random Access Memory), and a ROM (Read Only Memory).

[0026] The delivery margin calculation device 10 according to this embodiment can realize the delivery margin calculation process described below by having the hardware configuration shown in Fig. 1. Note that the hardware configuration shown in Fig. 1 is an example, and the delivery margin calculation device 10 may have, for example, multiple processors 15 or multiple memory devices 16. Furthermore, the delivery margin calculation device 10 may have various hardware other than the hardware shown in Fig. 1.

[0027] <Functional configuration of the delivery margin calculation device 10> The functional configuration of the delivery capacity calculation device 10 according to this embodiment is shown in Fig. 2. As shown in Fig. 2, the delivery capacity calculation device 10 according to this embodiment has an input unit 101, a selection unit 102, an allocation unit 103, a capacity calculation unit 104, and an output unit 105. Each of these units is realized, for example, by a process in which one or more programs installed in the delivery capacity calculation device 10 are executed by a processor 15.

[0028] Moreover, the delivery capacity calculation device 10 according to the present embodiment has a storage unit 106. The storage unit 106 is realized, for example, by the memory device 16. Note that the storage unit 106 may be realized, for example, by a storage device connected to the delivery capacity calculation device 10 via a communication network.

[0029] The input unit 101 receives the delivery data set {P n} n∈N and the delivery resource data set {V m} m∈M and the virtual delivery data set {Q k} k∈K and are input from the storage unit 106.

[0030] The selection unit 102 selects the virtual delivery data set {Q k} k∈K Virtual delivery data Q included in k Select one item.

[0031] The allocation unit 103 allocates the delivery data set {P n} n∈N and the delivery resource data set {V m} m∈M The allocation unit 103 allocates a delivery resource m to each delivery item n by solving a delivery planning problem using the above. kBy solving the delivery plan problem using the allocation results so far, a delivery resource is allocated to the virtual delivery item k. Note that at this time, there may be cases where no delivery resource m can be allocated to a certain delivery item n or a certain virtual delivery item k. This corresponds to cases where, for example, the delivery resource that should deliver the delivery item reaches its upper load capacity, or the delivery resource that should deliver the delivery item cannot reach the delivery destination during the delivery time.

[0032] The margin calculation unit 104 uses the allocation result of the virtual delivery piece data by the allocation unit 103 to calculate a margin of delivery capacity from the virtual delivery piece data of the virtual delivery pieces that have been allocated to the delivery resources.

[0033] The output unit 105 outputs to a predetermined output destination delivery margin data indicating the delivery margin calculated by the margin calculation unit 104. The output unit 105 may output the delivery margin data to any predetermined output destination, but may output the data to, for example, the storage unit 106, another program, or the like, the display device 12, or another device or other equipment connected via a communication network.

[0034] The storage unit 106 stores the delivery data set {P n} n∈N and the delivery resource data set {V m} m∈M and the virtual delivery data set {Q k} k∈K The storage unit 106 also stores various information such as the allocation result by the allocation unit 103 and delivery capacity data.

[0035] 2 shows an example of a functional configuration in the case where the delivery capacity calculation device 10 is realized by one device, the delivery capacity calculation device 10 may be realized by multiple devices. In this case, each functional unit shown in FIG. 2 may be distributed and arranged on multiple devices. For example, a first device and a second device that can communicate with each other via a communication network such as the Internet may exist, the first device may have the input unit 101, the selection unit 102, the capacity calculation unit 104, and the output unit 105, and the second device may have the allocation unit 103.

[0036] <Shipping margin calculation process> The delivery margin calculation process according to this embodiment will be described with reference to FIG. 3. The delivery margin calculation process is repeatedly executed at predetermined time intervals (for example, every hour). This is done by calculating the delivery item data set {P n} n∈N However, the delivery data set {P n} n∈N The delivery margin calculation process may be executed when the delivery data is changed. For example, the trigger may be when one delivery data item is added to the delivery data set, or when the number of delivery data items included in the delivery data set reaches N.

[0037] The input unit 101 receives a delivery data set {P n} n∈N and the delivery resource data set {V m} m∈M and the virtual delivery data set {Q k} k∈K are input from the storage unit 106 (step S101).

[0038] Next, the allocation unit 103 allocates the delivery data set {P n} n∈N and the delivery resource data set {V m} m∈MThe allocation unit 103 allocates a delivery resource m to each delivery item n by solving a delivery planning problem using the above (step S102). 1n , each delivery destination p 2n , each delivery time slot p 3n , each upper load capacity v 1m , each available time v 2m , each entry / exit location v 3m Each delivery item n is assigned to one of the delivery resources m by solving a delivery planning problem with the constraints, and a predetermined cost (e.g., distance, time, etc.) as an objective function. In other words, the assignment unit 103 assigns each delivery item n to one of the delivery resources m so as to minimize the cost under the constraints. However, there may be cases where a certain delivery item n cannot be assigned to any of the delivery resources m. The delivery planning problem can be solved by a known solution method.

[0039] In the following, if delivery item n is assigned to delivery resource m, then e nm = 1, otherwise e nm = 0, e nm The assignment result vector with the m-th element is e n In addition, the allocation result vector e n Let E be the set of (assignment result set). 1 That is, E 1 ={e n |n∈N}. This assignment result set E 1 is stored in the storage unit 106. For each n∈N, the allocation result vector e n Of the elements of e nm = 1. That is, if delivery n is assigned to delivery resource m, then e nm =1, e nm' = 0(m'∈M\{m}), and if delivery n is not assigned to any delivery resource m, then e for all m∈M. nm =0.

[0040] In the above delivery plan problem in step S102, it is assumed that a delivery plan per day is obtained by allocating delivery resource m to each delivery item n, but this does not necessarily have to be per day, and for example, it can be similarly applied to obtaining a delivery plan per week. In addition, in the above delivery plan problem, it is assumed that the allocation result does not change within a day or a week, but it can be similarly applied to a case where the allocation result can change for a certain time span. For example, if delivery items can be transshipped within a day (as a specific example, delivery items can be transshipped between the morning and afternoon), the delivery plan problem can be solved for each time span using the allocation result set for the previous time span.

[0041] Next, the selection unit 102 selects the virtual delivery data set {Q k} k∈K Unselected virtual delivery data Q k The virtual delivery data selected in this step is hereinafter referred to as “virtual delivery data Q k' " is expressed as ".

[0042] Next, the allocation unit 103 allocates the virtual delivery data Q selected in step S103 above. k' Using the allocation result set E representing the allocation results so far, the delivery resource m is allocated to the virtual delivery item k' by solving the delivery plan problem (step S104). Here, the allocation result set E is the allocation result set E 1 and the virtual delivery data Q selected so far k The allocation result set E of virtual delivery k corresponding to 2 The assignment result set E 2 The initial value of E 2 =φ.

[0043] That is, the allocation unit 103 combines the allocation result set E and the virtual delivery data Q selected in the above step S103. k' Collection locations included in q 1k' , shipping address q 2k' and delivery time slot q 3k' and each upper load capacity v 1m, each available time v 2m , each entry / exit location v 3m By solving a delivery planning problem with the constraints and a predetermined cost as an objective function, the virtual delivery item k' is assigned to one of the delivery resources m. This means that the virtual delivery item k' is further assigned to one of the delivery resources m without changing the assignment results of the already assigned delivery item n and virtual delivery item k. Note that there may be cases where the virtual delivery item k' is not assigned to any of the delivery resources m.

[0044] Then, the allocation unit 103 calculates the allocation result vector e k' Assign result set E 2 This adds the result set E 2 ={e k |k∈K'⊂K,K' is the index set of the virtual delivery data selected in step S103} is obtained. Here, when the virtual delivery k is assigned to the delivery resource m, e km = 1, otherwise e km = 0, the allocation result vector e k e km The m-th element of the allocation result vector e k Of the elements of e km There is at most one element for which =1.

[0045] Next, the selection unit 102 selects the virtual delivery data set {Q k} k∈K Unselected virtual delivery data Q k It is determined whether or not exists (step S105).

[0046] Virtual delivery data Q not selected in step S105 above k If it is determined that there is virtual delivery data Q, the selection unit 102 returns to step S103. k Each virtual delivery data Q k' Step S104 is repeatedly executed for each of the

[0047] On the other hand, the virtual delivery data Q that has not been selected in step S105 above k If it is determined that there is no virtual delivery data Q k The result set E represents the result of the allocation of 2 In other words, the margin calculation unit 104 calculates the delivery margin using the allocation result vector e k Virtual delivery data Q corresponding to k That is, the margin calculation unit 104 calculates the margin of delivery capacity from the virtual delivery item data Q k Calculate the delivery capacity from this.

[0048] For example, the spare capacity calculation unit 104 calculates an allocation result vector e having an element that takes the value 1 for each predetermined delivery area and time period. k Virtual delivery data Q corresponding to k And the delivery destination q is included in the delivery area 2k and the delivery time slots q included in that time slot 3k Virtual delivery data Q with k This allows the delivery capacity for each predetermined delivery area and time period to be calculated.

[0049] For example, the predetermined delivery areas are "A City", "B City", and "C City", and the predetermined time periods are "morning (8:00-12:00)", "afternoon 1 (13:00-17:00)", and "afternoon 2 (17:00-20:00)". In this case, for example, the virtual delivery data Q of the virtual delivery k assigned to any one of the delivery resources m is k There were five cases, which were as follows:

[0050] Q 1 =(q 11 ,q 21 ,q 31 )=(A city XX town, A city XX town 1-2-3, Afternoon 1 (13:00~17:00)) Q 2 =(q 12 ,q 22 ,q32 ) = (A city XX town, A city △△ town 1-3-4, Afternoon 1 (13:00~17:00)) Q 3 =(q 13 ,q 23 ,q 33 ) = (A city XX town, A city △△ town 2-3, afternoon 2 (17:00~20:00)) Q 4 =(q 14 ,q 24 ,q 34 ) = (B City, XX Town, B City, 1-1 XX Town, Morning (8:00~12:00)) Q 5 =(q 15 ,q 25 ,q 35 ) = (B City XX Town, B City XX Town 1-2, Morning (8:00~12:00)) In this case, the delivery capacity for the delivery area "City A" and time period "Afternoon 1 (13:00-17:00)" is calculated as "2", the delivery capacity for the delivery area "City A" and time period "Afternoon 2 (17:00-20:00)" is calculated as "1", and the delivery capacity for the delivery area "City B" and time period "Morning (8:00-12:00)" is calculated as "2". On the other hand, the delivery capacity for delivery areas and time periods other than these is calculated as "0".

[0051] Then, the output unit 105 outputs the delivery margin data representing the delivery margin calculated in the above step S106 to a predetermined output destination (step S107). Here, in general, the number of possible values ​​of a predetermined delivery area is I, the number of possible values ​​of a time period is J, and the delivery margin of the i-th delivery area and the j-th time period is x ij Then, the delivery capacity data is {x ij It can be expressed as |i=1,···,I,j=1,···,J}.

[0052] As described above, the delivery capacity calculation device 10 according to this embodiment can calculate the delivery capacity for each delivery area and time period. Therefore, the user of the delivery capacity calculation device 10 according to this embodiment can take various measures to improve delivery efficiency using these delivery capacity. Note that, as an example of such a measure, as will be described later, there is dynamic pricing, which dynamically sets delivery fees according to the delivery capacity.

[0053] <Application Examples> Hereinafter, as one application example of the delivery margin calculation device 10 according to this embodiment, a case where dynamic pricing is performed using delivery margin for each delivery area and time period will be described. This dynamic pricing may be performed by the delivery margin calculation device 10, or may be performed by another device or device different from the delivery margin calculation device 10. In other words, the delivery fee calculation unit that calculates the delivery fee according to the delivery margin for each delivery area and time period as described later may be included in the delivery margin calculation device 10, or may be included in another device or device different from the delivery margin calculation device 10.

[0054] For example, assume that the delivery capacity for each delivery area and time period is obtained at a certain point in time, "as of 15:00 on a certain date," as shown in the upper diagram of Figure 4. In the example shown in the upper diagram of Figure 4, "none" indicates that the delivery capacity is "0."

[0055] At this time, for example, as shown in the lower diagram of Figure 4, the delivery fee is calculated according to the delivery capacity for each delivery area and time period. In other words, the more the delivery capacity, the lower the delivery fee, and the less the delivery capacity, the higher the delivery fee. In the example shown in the lower diagram of Figure 4, "-" indicates that there is no delivery capacity and no more deliveries can be accepted.

[0056] More generally, the delivery capacity data at a certain time t is expressed as {x ij (t) For |i=1,···,I,j=1,···,J}, in dynamic pricing, the delivery fee data {yij (t) |i=1,···,I,j=1,···,J}, where y ij (t) =f(x ij (t) ) is the delivery fee for the i-th delivery area and j-th time slot at time t. Also, f(x) is a function for determining the delivery fee, and is a known function used in dynamic pricing. For f(x), for example, f(0) = +∞, and a decreasing function or a step function in which f(x) becomes smaller as x becomes larger, can be used.

[0057] By applying this dynamic pricing, it is possible to increase delivery efficiency by setting low delivery fees for delivery areas and time periods with a large delivery capacity. On the other hand, it is possible to prevent excessive or inefficient operation of delivery resources, for example, by setting high delivery fees for delivery areas and time periods with a small delivery capacity, and it is also possible to suppress the increase in costs associated with the operation of delivery resources.

[0058] This application example assumes that the delivery margin for each delivery area and time period is calculated by the delivery margin calculation process shown in Fig. 3, but is not necessarily limited to this, and can be similarly applied to the case where the delivery margin for each delivery area and time period is calculated by some method (for example, the delivery margin calculation process shown in Fig. 4 described later or other arbitrary delivery margin calculation process). That is, every time the delivery margin calculation device 10 (or another device or equipment different from it) inputs the delivery margin for each delivery area and time period calculated by an arbitrary method through the input unit 101, this delivery margin calculation device 10 (or another device or equipment different from it) calculates the delivery fee and can perform the above-mentioned dynamic pricing.

[0059] <Modification> A modification of this embodiment will now be described.

[0060] <Variation 1> In this embodiment, the virtual delivery data set {Qk} k∈K is created in advance and given to the delivery capacity calculation device 10. For example, each virtual delivery data Q k may be created on demand. For example, a minimal virtual delivery data set {Q k} k∈K is created in advance and given to the delivery capacity calculation device 10, and the other virtual delivery data Q k may be created each time in step S103 of the delivery margin calculation process as necessary. k} k∈K is not created in advance, and all virtual delivery data Q k may be created each time in step S103 of the delivery margin calculation process.

[0061] <<Variation 2>> In this embodiment, in step S105 of the delivery margin calculation process, the virtual delivery data set {Q k} k∈K Unselected virtual delivery data Q k However, it may be possible to determine whether a predetermined condition is satisfied, for example. Such a condition may be, for example, that all delivery resources have reached their upper load limit, that all delivery resources have no available time, etc.

[0062] <Modification 3> In this embodiment, the unit of the delivery capacity is "number of items", but this is not limited to this. For example, if the amount of delivery items (e.g., the size and weight of the delivery items) are included in the delivery item data and the virtual delivery item data, the unit of the delivery capacity may be "size" or "weight". In this case, when calculating the delivery capacity in step S106 of the delivery capacity calculation process, the virtual delivery item data Q of the virtual delivery item k assigned to any delivery resource m k The delivery capacity can be calculated from the cargo volume (size, weight, etc.) included in the delivery area. Specifically, for each predetermined delivery area and time period, an allocation result vector e k Virtual delivery data Q corresponding to kAnd the delivery destination q is included in the delivery area 2k and the delivery time slots q included in that time slot 3k Virtual delivery data Q with k The sum of the cargo volumes can be regarded as the delivery capacity for that delivery area and that time period.

[0063] <Modification 4> As a modified example of the delivery capacity calculation process, a case where delivery capacity is calculated for a combination of possible values ​​of a predetermined delivery area and possible values ​​of a time period will be described with reference to Fig. 5. Fig. 5 is a flow chart showing an example of a delivery capacity calculation process according to the modified example. Note that the points not specifically described in this modified example 4 may be the same as the delivery capacity calculation process shown in Fig. 3.

[0064] Steps S201 to S202 in FIG. 5 are similar to steps S101 to S102 in FIG. 3, and therefore the description thereof will be omitted.

[0065] The selection unit 102 selects one unselected combination (i, j) of delivery region i and time zone j from the Cartesian product set {1, . . . , I} × {1, . . . , J} of the delivery region set and the time zone set (step S203).

[0066] Next, the selection unit 102 selects the virtual delivery data set {Q k} k∈K Unselected virtual delivery data Q k And the delivery destination q 2k is included in delivery region i and delivery time slot q 3k is the virtual delivery data Q included in time period j k The virtual delivery data selected in this step is hereinafter referred to as “virtual delivery data Q k' " is expressed as ".

[0067] Next, the allocation unit 103 allocates the virtual delivery data Q selected in step S204 above. k'and an allocation result set E representing the allocation results up to now, a delivery resource m is allocated to the virtual delivery item k' by solving a delivery plan problem (step S205).

[0068] Next, the allocation unit 103 allocates the virtual delivery data Q selected in step S204 above. k' It is determined whether or not the request can be allocated to any one of the delivery resources m (step S206).

[0069] In step S206 above, the virtual delivery data Q k' If it is determined that the virtual delivery data Q can be allocated to any one of the delivery resources m, the process returns to step S204. k' Steps S204 and S205 are repeatedly executed until it is determined that the packet can be allocated to any one of the delivery resources m.

[0070] On the other hand, in step S206, the virtual delivery data Q k' If it is not determined that the destination q can be allocated to any of the delivery resources m, the process proceeds to step S207. 2k is included in delivery region i and delivery time slot q 3k Unselected virtual delivery data Q included in time period j k If not, the process also proceeds to step S207.

[0071] The margin calculation unit 104 calculates the virtual delivery data Q k The result set E represents the result of the allocation of 2 This delivery capacity is calculated as the delivery capacity x corresponding to the combination (i, j) of the delivery area i and the time zone j (step S207). ij It is.

[0072] Next, the selection unit 102 determines whether or not there is an unselected (i, j) in the Cartesian product {1, . . . , I} × {1, . . . , J} of the delivery area set and the time zone set (step S208).

[0073] If it is determined in step S208 that there is an unselected (i, j), the selection unit 102 selects the virtual delivery data set {Q k} k∈K In other words, the selection unit 102 resets the selection status of the virtual delivery data set {Q k} k∈K All virtual shipment data included in Q k is regarded as unselected. Then, the selection unit 102 returns to the above step S203. As a result, the above steps S203 to S207 are repeatedly executed for each (i, j) until there is no unselected (i, j).

[0074] 5 is the same as step S107 in FIG. 3, so the description thereof will be omitted. In this manner, as in this modified example, by allocating delivery resources to the virtual delivery item data for each combination (i, j) of delivery area i and time zone j, the delivery margin x ij It is also possible to calculate

[0075] The present invention is not limited to the above-described embodiments specifically disclosed, and various modifications, changes, combinations with known technologies, etc. are possible without departing from the scope of the claims. [Explanation of symbols]

[0076] 10. Delivery capacity calculation device 11 Input Devices 12 Display device 13 External I / F 13a Recording media 14 Communication I / F 15 Processors 16 Memory Devices 17 Bus 101 Input section 102 Selection section 103 Allocation Section 104 Reserve Calculation Section 105 Output section 106 Storage section

Claims

1. an input unit for inputting a delivery item data set constituted by delivery item data representing delivery items to be delivered and a delivery resource data set constituted by delivery resource data representing delivery resources for delivering the delivery items; a first allocation unit that calculates a first allocation result indicating an allocation result of delivery resources to each delivery by solving a delivery plan problem based on each delivery item data constituting the delivery item data set and each delivery resource data constituting the delivery resource data set; a second allocation unit that calculates a second allocation result indicating an allocation result of delivery resources to each of one or more virtual delivery items by repeatedly solving a delivery plan problem based on one or more virtual delivery item data each representing one or more virtual delivery items and the first allocation result; a margin calculation unit that calculates a margin of delivery representing a margin of delivery that the delivery resource can deliver based on the second allocation result; A delivery margin calculation device having the above structure.

2. The virtual delivery data includes at least a delivery destination of the delivery item and a delivery time period to the delivery destination, The spare capacity calculation unit is 2. The delivery capacity calculation device according to claim 1, further comprising: a delivery capacity calculation unit that calculates a delivery capacity for each predetermined delivery area and time period from a delivery destination and a delivery time period included in virtual delivery item data representing a virtual delivery item allocated to any one of the delivery resources based on the second allocation result.

3. The spare capacity calculation unit is 3. The delivery capacity calculation device according to claim 2, wherein the number of virtual delivery data representing virtual deliveries assigned to any one of the delivery resources, the number of virtual delivery data whose delivery destination is included in the delivery area and whose delivery time period is included in the time period, is calculated as the delivery capacity for the delivery area and the time period.

4. The virtual delivery data further includes the load of the delivery, The spare capacity calculation unit is 3. The delivery capacity calculation device according to claim 2, wherein the total volume of virtual delivery data representing virtual deliveries assigned to any one of the delivery resources, the delivery destination of which is included in the delivery area and the delivery time period of which is included in the time period, is calculated as the delivery capacity of the delivery area and the time period.

5. The delivery capacity calculation device according to claim 4 , wherein the cargo volume is a size or weight of the delivery item.

6. A fee calculation unit calculates a delivery fee for each delivery area and each time a delivery margin is calculated based on the delivery margin, The delivery capacity calculation device according to claim 3 , wherein the delivery capacity calculation device repeatedly calculates the delivery capacity for each delivery area and time period at each predetermined time.

7. The second allocation unit, 7. The delivery capacity calculation device according to claim 1, wherein the second allocation result is calculated based on each of one or more given virtual delivery item data and the first allocation result.

8. The second allocation unit, The delivery capacity calculation device according to any one of claims 1 to 6, wherein the second allocation result is calculated based on virtual delivery item data created each time the delivery plan problem is repeatedly solved and the first allocation result.

9. An input step of inputting a delivery item data set constituted by delivery item data representing delivery items to be delivered, and a delivery resource data set constituted by delivery resource data representing delivery resources for delivering the delivery items; A first allocation procedure for calculating a first allocation result indicating an allocation result of a delivery resource to each delivery by solving a delivery plan problem based on each delivery item data constituting the delivery item data set and each delivery resource data constituting the delivery resource data set; a second allocation procedure for calculating a second allocation result indicating an allocation result of delivery resources to each of one or more virtual delivery items by repeatedly solving a delivery plan problem based on one or more virtual delivery item data each representing one or more virtual delivery items and the first allocation result; A margin calculation step of calculating a margin for delivery representing a margin for deliveries that the delivery resources can deliver based on the second allocation result; A computer-implemented method for calculating shipping margin.

10. An input step of inputting a delivery item data set constituted by delivery item data representing delivery items to be delivered, and a delivery resource data set constituted by delivery resource data representing delivery resources for delivering the delivery items; A first allocation procedure for calculating a first allocation result indicating an allocation result of a delivery resource to each delivery by solving a delivery plan problem based on each delivery item data constituting the delivery item data set and each delivery resource data constituting the delivery resource data set; a second allocation procedure for calculating a second allocation result indicating an allocation result of delivery resources to each of one or more virtual delivery items by repeatedly solving a delivery plan problem based on one or more virtual delivery item data each representing one or more virtual delivery items and the first allocation result; A margin calculation step of calculating a margin for delivery representing a margin for deliveries that the delivery resources can deliver based on the second allocation result; A program that causes a computer to execute the following.

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