Information processing apparatus and information processing method

Abstract

To provide a technique for generating an efficient delivery plan which can be operated at a site.SOLUTION: An information processing apparatus according to an aspect of the present disclosure includes a processor configured to receive a delivery request from each of a plurality of stores, generate, in response to a delivery request from a first store among the plurality of stores, a delivery plan by an exclusive delivery service that loads a package of a loadable amount and delivers the package to only the first store, and generate, in response to a delivery request from a second store among the plurality of stores, a delivery plan by an exclusive delivery service that loads a package of a loadable amount and delivers the package to only the second store. A delivery plan is created with the consolidated shipment to deliver to two or more stores.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device and an information processing method. [Background technology]

[0002] Patent Document 1 proposes a system for assigning delivery personnel to a logistics center. Specifically, this system identifies a logistics center based on user input, references delivery plan information related to the identified logistics center, delivery personnel assignment conditions, and job information for each delivery personnel, and assigns one or more delivery personnel to the logistics center based on the referenced information. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-013522 Summary of the Invention [Problem to be solved by the invention]

[0004] One of the objectives of the present disclosure is to provide a technique for generating efficient dispatch plans that can be implemented in the field. [Means for solving the problem]

[0005] An information processing device according to a first aspect of the present disclosure includes a control unit. The control unit is configured to receive delivery requests from multiple stores, generate a delivery plan for a first store among the multiple stores, where the requested amount of cargo is equal to or greater than the load capacity of one vehicle, using a dedicated vehicle to load the loadable amount of cargo and deliver it to only that store, and generate a delivery plan for a mixed-load vehicle to deliver to two or more stores, where the remaining portion of the delivery request from the first store excluding the portion for which the delivery plan was created using the dedicated vehicle and a second store, where the requested amount of cargo is less than the load capacity of one vehicle. A MaaS (Mobility as a Service) provision method may be configured using the information processing device.

[0006] An information processing method according to a second aspect of the present disclosure is executed by a computer. The information processing method includes receiving delivery requests from a plurality of stores, generating a delivery plan for a first store among the plurality of stores, the first store requesting a quantity of cargo equal to or greater than the load capacity of one vehicle, using a dedicated vehicle to load the quantity of cargo and deliver it to only that store, and generating a delivery plan for a portion of the delivery request from the first store excluding the portion for which the delivery plan has been created using the dedicated vehicle and a second store requesting a quantity of cargo less than the load capacity of one vehicle, using a consolidated vehicle to deliver to two or more stores. [Effects of the Invention]

[0007] According to the present disclosure, it is possible to generate a delivery plan that is operational and efficient on-site. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 schematically illustrates an example of a situation to which the present disclosure is applied. [Figure 2] FIG. 2 schematically illustrates an example of a scene in which a delivery plan according to the present disclosure is generated. [Figure 3] FIG. 3 is a diagram illustrating an example of the configuration of delivery person information and store information according to the present disclosure. [Figure 4]FIG. 4 schematically illustrates an example of a hardware configuration of a server device according to the present disclosure. [Figure 5] FIG. 5 is a flowchart illustrating an example of a processing procedure for generating a delivery plan by the server device of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0009] In conventional methods, delivery plans are sometimes created using mixed-load deliveries from a logistics center (distribution base) to multiple stores. Mixed-load deliveries increase the degree of flexibility in deliveries, potentially contributing to the optimization of the overall delivery plan. However, allowing mixed-load deliveries results in a vast number of combinations of delivery personnel (vehicles), packages to be delivered, destination stores, and delivery order, increasing the amount of calculation required for the delivery plan and complicating the delivery plan. A complex delivery plan can lead to problems, such as delivery personnel being unable to complete delivery tasks as planned or delays causing frequent plan changes, making on-site operation difficult. In other words, allowing mixed-load deliveries throughout the entire delivery plan can make it difficult to generate a delivery plan that can be implemented on-site.

[0010] In contrast, an information processing device according to a first aspect of the present disclosure includes a control unit configured to receive delivery requests from each of a plurality of stores, and generate a delivery plan for a first store among the plurality of stores, where the requested amount of cargo is equal to or greater than the load capacity of one vehicle, using a dedicated vehicle to load the loadable amount of cargo and deliver it to only that one store, and generate a delivery plan for a mixed vehicle to deliver to two or more stores, where the remaining portion of the delivery request from the first store excluding the portion for which the delivery plan has been created using the dedicated vehicle is delivered, and where the requested amount of cargo is less than the load capacity of one vehicle, is delivered to a second store.

[0011] In a first aspect of the present disclosure, delivery by dedicated service is planned preferentially for a store (first store) requesting delivery of an amount of cargo that exceeds the load capacity of one vehicle. Then, delivery by consolidated service is planned for the portion not included in the delivery plan using dedicated service and for a store (second store) requesting delivery of an amount of cargo that is less than the load capacity of one vehicle. This simplifies the delivery plan by prioritizing dedicated service, and improves delivery efficiency by planning delivery by consolidated service for portions for which dedicated service is inefficient. Therefore, according to the first aspect of the present disclosure, it is expected that a delivery plan that is operational and efficient on site can be generated.

[0012] As another form of the information processing device according to the above aspect, one aspect of the present disclosure may be an information processing method that realizes all or part of the above components, a program, or a storage medium that stores such a program and is readable by a machine such as a computer. Here, a machine-readable storage medium is a medium that stores information such as a program by electrical, magnetic, optical, mechanical, or chemical action.

[0013] For example, an information processing method according to a second aspect of the present disclosure is executed by a computer. The information processing method includes receiving delivery requests from each of a plurality of stores, generating a delivery plan for a delivery request from a first store among the plurality of stores, the first store requesting a quantity of cargo equal to or greater than the load capacity of one vehicle, using a dedicated vehicle to load the loadable quantity of cargo and deliver it to only that store, and generating a delivery plan for a portion of the delivery request from the first store excluding the portion for which the delivery plan has been created using the dedicated vehicle and a delivery request from a second store requesting a quantity of cargo less than the load capacity of one vehicle, using a consolidated vehicle to deliver to two or more stores.

[0014] [1 Application example] 1 schematically illustrates an example of a scenario in which the present disclosure is applied. The server device 1 according to this embodiment is one or more computers configured to execute a process of generating a delivery plan 50 in response to a delivery request DR from each store S and instructing each delivery person DP to perform a delivery task in accordance with the generated delivery plan 50. The server device 1 is an example of an information processing device according to the present disclosure.

[0015] In this embodiment, the server device 1 receives a delivery request DR from each of a plurality of stores S. In response to the delivery request DR from a first store among the plurality of stores S, which requests an amount of cargo equal to or greater than the load capacity of one vehicle, the server device 1 generates a delivery plan 50 using a dedicated vehicle that loads the load capacity of cargo and delivers it to only that one store. The dedicated vehicle is called a short flight, a charter flight, or the like. The server device 1 generates a delivery plan 50 using a consolidated delivery service to deliver to two or more stores for the remaining portion of the delivery request DR of the first store excluding the portion for which the delivery plan 50 has been created using a dedicated delivery service and for the delivery request DR of the second store for which the requested amount of cargo is less than the load capacity of one vehicle. That is, the server device 1 generates a delivery plan 50 for the delivery request DR of the first store by giving priority to a dedicated delivery service. The server device 1 generates a delivery plan 50 using a consolidated delivery service for the remaining cargo of the delivery request DR of the first store that has not been allocated to a dedicated delivery service and for the delivery request DR of the second store. The remainder of the delivery request DR that has not been allocated using a consolidated delivery service may be processed in any manner, such as by allocating it to a dedicated delivery service. The server device 1 outputs the generated delivery plan 50.

[0016] Each store S may send a delivery request DR to the server device 1 via the store terminal 30. When generating the delivery plan 50, the server device 1 may refer to any information such as the delivery person information 400 and the store information 450. Each delivery person DP loads packages onto a vehicle T at the logistics center DC in accordance with the delivery plan 50 and performs a delivery task of delivering the packages to the designated store. Outputting the delivery plan 50 may include sending instructions to perform the delivery task to the terminal of the delivery person DP. As long as the delivery person DP can check the instructions to perform the delivery task while working, the terminal of the delivery person DP may be selected appropriately depending on the embodiment. In FIG. 1, the user terminal 21 and the in-vehicle terminal 22 are examples of the terminal of the delivery person DP. The user terminal 21 is one or more computers held by the delivery person DP. The user terminal 21 may be, for example, a smartphone, a tablet terminal, a laptop PC (Personal Computer), a dedicated terminal, etc. The delivery person DP If the delivery person DP holds multiple user terminals, the multiple user terminals may be regarded as one user terminal 21. The in-vehicle terminal 22 is one or more computers mounted on the vehicle T used by the delivery person DP. The server device 1 may send instructions to perform delivery tasks assigned in the delivery plan 50 to at least one of the user terminal 21 and the in-vehicle terminal 22.

[0017] FIG. 2 schematically illustrates an example of a scenario in which a delivery plan 50 according to the present disclosure is generated. The scenario in FIG. 2 assumes that the cargo amounts in the delivery requests DR for stores S1 and S2 exceed the load capacity of one vehicle, and that the cargo amount in the delivery request DR for store S3 is less than the load capacity of one vehicle. Stores S1 and S2 are examples of first stores, and store S3 is an example of a second store. It is also assumed that the cargo amount in the delivery request DR for store S3 is 0.4 (40%) of the load capacity, and that the load capacity is set to 0.9 (90%).

[0018] The server device 1 may generate a delivery plan 50 using dedicated vehicles for the delivery request DR of the first store until the remaining amount of cargo falls below the load capacity of one vehicle. In the example of Figure 2, after a delivery plan 50 using dedicated vehicles for K shipments for store S1 and L shipments for store S2 is generated, a situation is assumed in which the remaining delivery request DR of store S1 is 0.3 (30%) of the load capacity, and the remaining delivery request DR of store S2 is 0.5 (50%) of the load capacity.

[0019] After the delivery plan 50 using the dedicated service is created, the server device 1 may generate a delivery plan 50 using a consolidated service for the remaining parcels in the delivery request DR of the first store (parcels not allocated to the dedicated service) and the delivery request DR of the second store. The delivery plan 50 for the consolidated service may be generated based on any index, such as increasing the amount of parcels loaded onto one vehicle. For example, if an index is given that prioritizes increasing the amount of parcels loaded onto one vehicle, the server device 1 may generate a delivery plan 50 for delivering the remaining parcels in the delivery request DR of store S2 (0.5 parcels) and the delivery request DR of store S3 (0.4 parcels) by consolidated service.

[0020] As described above, in this embodiment, delivery by dedicated service is planned with priority for the first store requesting more cargo than can be loaded onto one vehicle. Then, delivery by consolidated service is planned for the remaining cargo at the first store and the second store requesting less cargo than can be loaded onto one vehicle. This simplifies the delivery plan 50 by prioritizing dedicated service, and also allows for the use of consolidated service for portions that are inefficient when using dedicated service (for example, delivery requests for fractional amounts that do not fill a dedicated service). Therefore, according to this embodiment, it is expected that an efficient delivery plan 50 that can be used on-site can be generated.

[0021] (Delivery request) The delivery request DR may include a specification of the items to be delivered and the quantity of the goods. The delivery request DR may further include a specification of the delivery destination location. The delivery request DR may further include information indicating the available delivery times (the start time and end time of delivery). Each store S may use a store terminal 30 to send the delivery request DR to the server device 1. The store terminal 30 may be, for example, a smartphone, a tablet terminal, a laptop PC, a general-purpose PC, a dedicated terminal, etc.

[0022] (loading capacity) The load capacity of a dedicated delivery may be determined appropriately depending on the embodiment. The load capacity of a dedicated delivery may be the upper limit of the amount of cargo that can be loaded onto vehicle T (load rate 100%), or may be an amount close to the upper limit. An amount close to the upper limit may be defined, for example, as an amount slightly less than the upper limit, such as 90% load capacity, as in the example of FIG. 2 above. Loading the load capacity of a dedicated delivery may mean loading an amount of cargo at or near the upper limit. The load capacity may be a fixed value or a variable value. The load capacity may be specified by a user or may be defined within a program. The load capacity may be the same for each vehicle T, or may be different for at least some of the vehicles T. When vehicles T used for delivery have different load capacities, the reference load capacity may be determined arbitrarily. In one example, the load capacity may be determined for each vehicle T. In another example, the load capacity may be determined based on a uniform standard, such as using the vehicle with the least load capacity as the reference.

[0023] (Delivery plan) The logistics center DC is a base for performing delivery operations such as receiving, storing, packaging, and shipping goods. The area to which packages are delivered from the logistics center DC may be divided into multiple delivery areas. Each delivery area may include one or more stores S to which the packages are delivered. Each store S belonging to one of the delivery areas of the logistics center DC may use a store terminal 30 to generate a delivery request DR for the logistics center DC and send the generated delivery request DR to the server device 1. The delivery task may be to deliver packaged packages to a specified location in response to the delivery request DR from each store S. In detail, performing the delivery task may be to perform a series of delivery operations at the logistics center DC, such as loading packaged packages into a vehicle T, driving the vehicle T to one or more stores S, and delivering the packages to each store S.

[0024] The delivery person DP uses a vehicle T to perform one or more delivery tasks. In the case of a dedicated delivery, the delivery person DP delivers a package to one delivery destination. In the case of a mixed delivery, the delivery person DP delivers a package to each of two or more delivery destinations. The delivery person DP and the vehicle T may be assigned statically or dynamically on a one-to-one basis. The delivery person DP and the vehicle T are assigned appropriately to each delivery area depending on, for example, the business company to which the delivery person DP belongs. The server device 1 may generate a delivery plan 50 by determining a combination of a delivery destination (store S) and a vehicle T (delivery person DP) for each delivery area. Generating the delivery plan 50 may include assigning one or more delivery tasks to the delivery person DP. The delivery person DP may be instructed to perform one or more delivery tasks according to the generated delivery plan 50. The delivery person DP may perform the delivery task according to the instructions. The server device 1 may manage a series of information processing and data related to this delivery work on a logistics center DC basis.

[0025] (Various information) The delivery operations of the distribution center DC may be managed appropriately using information. As long as the delivery operations can be managed, the configuration of the information related to the delivery operations of the distribution center DC is not particularly limited and may be determined appropriately depending on the embodiment. The information related to the delivery operations of the distribution center DC may be, for example, For example, it may include information about the delivery person DP, information about the vehicle T, information about the delivery destination (store S, etc.), etc. In this embodiment, the information about the delivery person DP and the information about the vehicle T is stored as delivery person information 400, and information about the store S, which is the delivery destination, is stored as store information 450.

[0026] FIG. 3 schematically illustrates an example of the configuration of delivery person information 400 and store information 450 according to this embodiment. As illustrated, in one example, the delivery person information 400 may include the identification information, attribute information, delivery skills, schedule, work status information, etc. of the delivery person DP. The identification information may include, for example, the identifier (ID) of the delivery person DP, the name, and the name of the vehicle T. The attribute information may include, for example, the load capacity that can be loaded onto the vehicle T. The delivery skills indicate the ability of the target delivery person DP to perform delivery tasks. The delivery skills may be specified by the number of years of delivery experience, the total delivery volume, an evaluation input by a manager, or the delivery person DP's self-declaration. The delivery skills may be specified by any method, such as free words or item selection. The schedule (schedule information) may include, for example, operation information and assignment information. The operation information may include, for example, the working days and working hours of the delivery person DP. The assignment information may include information on delivery tasks assigned to the delivery person DP. The work status information may include, for example, location information (current location), status (e.g., loading luggage, moving, delivery completed, etc.), and the like.

[0027] In addition, in one example, the store information 450 may include identification information, attribute information, etc. of the store S. The identification information may include, for example, an identifier (ID) or name of the store S. The attribute information may include, for example, location information of the store S and a set value for the time when the store S can receive goods. The delivery request DR from each store S may be stored in the store information 450. The data format of the delivery person information 400 and the store information 450 is not particularly limited and may be selected appropriately depending on the embodiment. Furthermore, the delivery person information 400 and the store information 450 may be stored for each delivery area.

[0028] The delivery person information 400 and the store information 450 may be referenced as appropriate when generating the delivery plan 50. Among the delivery person information 400 and the store information 450, static information such as identification information and attribute information may be registered in advance by user input or the like. Meanwhile, dynamic information such as the schedule, work status information, and delivery request DR may be updated in real time in response to the allocation of delivery tasks when the delivery plan 50 is generated, notifications from the terminals of the delivery person DP (user terminal 21, in-vehicle terminal 22), notifications from the vehicle T, and the like. In the above example, vehicle information such as the name of vehicle T and the load capacity that can be carried is included in the delivery person information 400, but the information configuration is not limited to this example. In another example, the vehicle information and the delivery person information 400 may be configured separately. The units for storing each piece of information are not limited to the example of this embodiment and may be changed as appropriate depending on the embodiment.

[0029] (Delivery task assignment) Delivery tasks may be assigned to delivery personnel DPs by any method. A known method may be used to assign delivery tasks to delivery personnel DPs. Delivery tasks may be generated appropriately in response to delivery requests DR from one or more stores S, while prioritizing dedicated deliveries for delivery requests DR from a first store and mixed-load deliveries for delivery requests DR from a second store, so as not to exceed the load capacity of a single vehicle T. The server device 1 assigns delivery tasks from the logistics center DC to one or more stores S during free time within the working hours of the delivery personnel DPs, so that at least a portion of the delivery requests DR from any of the stores S are processed within the working hours of the delivery personnel DPs indicated in the schedule. That is, the server device 1 assigns delivery tasks to delivery personnel DPs by matching the delivery requests DR from each store S with the delivery personnel DPs. The server device 1 may match the delivery requests DR with the delivery personnel DPs using at least one of a rule-based model and a trained model (a trained machine learning model).

[0030] The rule-based model generates inference results (in this embodiment) from given inputs according to rules. The machine learning model is configured to derive a calculation result (the allocation of delivery tasks). The allocation rules may be set as appropriate. The machine learning model is configured to have one or more calculation parameters that can be adjusted by machine learning. The one or more calculation parameters are used to calculate the desired inference (in this embodiment, the allocation of delivery tasks). The machine learning model may be configured, for example, by a neural network, a regression model, a decision tree model, a support vector machine, or other functional formula (calculation model). The machine learning method may be selected as appropriate depending on the machine learning model employed (e.g., backpropagation). Training the machine learning model involves adjusting (optimizing) the values ​​of the calculation parameters using training samples. The machine learning model may be trained as appropriate to acquire the ability to allocate the delivery tasks to the delivery personnel DP. The trained model may be a large-scale model (e.g., a large-scale language model) capable of in-context learning.

[0031] The server device 1 may use the attribute information (the amount of cargo that can be loaded onto the vehicle T), delivery skills, schedule, and work status information in the delivery person information 400, the attribute information in the store information 450, and the delivery request DR to determine the allocation of delivery tasks to the delivery person DP, while prioritizing dedicated deliveries for the first store and mixed-load deliveries for the second store. Note that the information used to allocate delivery tasks is not limited to these examples and may be changed as appropriate depending on the embodiment. In another example, the server device 1 may further use other information, such as inventory information from the logistics center DC, to determine the allocation of delivery tasks to the delivery person DP.

[0032] In one example, the delivery plan 50 for a consolidated shipment may be generated based on any index, as described above. The index used for the delivery tasks of a consolidated shipment may be determined appropriately depending on the embodiment. The index used for generating the delivery tasks of a consolidated shipment may include, for example, increasing the amount of cargo loaded onto one vehicle, shortening the total distance traveled from the logistics center DC to each store (total driving distance), reducing the number of destination stores, prioritizing stores with the closest end time for receiving goods, etc. In one example, when a rule-based model is used to generate the delivery plan 50, rules corresponding to the index used for generating the consolidated shipment may be defined appropriately. When a machine learning model is used, true values ​​of allocations that match the index used may be given to training samples, and the machine learning model may be trained to learn the correspondence between the given true values ​​and the training samples.

[0033] In one example, for the delivery plans 50 for dedicated and mixed shipments, at least one of each store S and the manager may set in advance at least one of acceptance conditions and rejection conditions for each delivery person DP. The manager may be, for example, a supervisor of the delivery person DP. The acceptance conditions are conditions that allow the assignment of delivery tasks, and the rejection conditions are conditions that prohibit the assignment of delivery tasks. When acceptance conditions are set, the server device 1 may create the delivery plan 50 so that delivery tasks are assigned only to delivery people who meet the set conditions. When rejection conditions are set, the server device 1 may create the delivery plan 50 so that delivery tasks for the target store are not assigned to delivery people who meet the set conditions, but to other delivery people. The acceptance conditions and rejection conditions may be set for any information that can select a delivery person DP. For example, the acceptance conditions and rejection conditions may be set for the delivery skills of the delivery person DP.

[0034] In one example, generating a delivery plan 50 for a mixed load delivery may include preferentially assigning delivery tasks for mixed load delivery to a delivery person with a high delivery skill level among multiple delivery person DPs. Because mixed load delivery involves unloading at two or more stores, if a delivery person with low delivery skills is in charge, there is a high possibility of delays or other problems occurring. In contrast, according to one example of this embodiment, preferentially assigning mixed load delivery to a delivery person with high delivery skills increases the likelihood that delivery tasks for mixed load delivery will be properly performed. This makes it possible to expect that the generated delivery plan 50 will be properly implemented.

[0035] In one example, generating a delivery plan 50 by a dedicated delivery service is performed by selecting a delivery person DP from among a plurality of delivery persons DP. This may include preferentially allocating delivery tasks on dedicated flights to delivery personnel with low delivery skills. Dedicated flights have fewer delivery destinations than mixed-load flights, making it easier to carry out delivery tasks. According to one example of this embodiment, by preferentially allocating relatively easy delivery tasks to delivery personnel with low delivery skills, it is possible to optimize the operation of the overall delivery plan 50 (i.e., to allocate the right person to the right job).

[0036] The level of delivery skill of each delivery person DP may be appropriately determined depending on the information format of the delivery skill included in the delivery person information 400. In a typical example, delivery skill may be defined by a numerical value such as years of experience, delivery volume, or level, with a higher numerical value indicating a higher delivery skill. In this case, if the delivery skill of the target delivery person exceeds a threshold, the delivery skill of the target delivery person may be determined to be high. If the delivery skill is below the threshold, the delivery skill of the target delivery person may be determined to be low. The threshold for evaluating high delivery skill and the threshold for evaluating low delivery skill may be the same or different. The delivery skill of each delivery person DP may be evaluated on a two-level scale of high and low, or on three or more levels (e.g., high, average, low, etc.).

[0037] In one example, generating a delivery plan 50 using a consolidated shipment may include preferentially generating a delivery plan 50 for the delivery request DR of the second store among the remaining portion of the delivery request DR of the first store and the delivery request DR of the second store. Prioritizing the delivery request DR of the second store means that, when determining the load of cargo on the consolidated shipment, parcels in the delivery request DR of the second store are preferentially assigned to the consolidated shipment compared to the remaining parcels in the delivery request DR of the first store. In the present disclosure, since the delivery plan 50 using a dedicated shipment is preferentially generated, generation of the delivery plan 50 using the consolidated shipment may be delayed. Since the delivery task is performed by the dedicated shipment, at least some parcels are delivered to the first store. On the other hand, delivery of parcels to the second store may be delayed. Therefore, in one example of the present embodiment, by prioritizing the second store when generating a delivery plan 50 using a consolidated shipment, delays in delivery of parcels to the second store can be eliminated.

[0038] In addition, if there is a remaining portion of the delivery request DR of each store S that has not been allocated to a dedicated flight or a consolidated flight using the above method, a delivery plan for the remaining portion may be generated using any method. In one example, the server device 1 may generate a delivery plan for the remaining portion using a dedicated flight. For example, in the example of Figure 2 above, if the remainder of the delivery request DR of store S2 and the delivery request DR of store S3 are allocated to a consolidated flight, and the remainder of the delivery request DR of store S1 (0.3 parcels) is not allocated to a consolidated flight, the remaining parcels of the delivery request DR of store S1 may be allocated to a dedicated flight. In another example, the remaining portion may be processed when a new delivery request is received from each store S and a delivery plan for the new delivery request is generated.

[0039] [2 Configuration Examples] 4 is a schematic diagram showing an example of the hardware configuration of the server device 1 according to this embodiment. The server device 1 according to this embodiment is a computer in which a control unit 11, a storage unit 12, a communication interface 13, and a drive 14 are electrically connected.

[0040] The control unit 11 includes a CPU (Central Processing Unit), a RAM (Random Access Memory ), ROM (Read Only Memory), etc., and is configured to execute any information processing based on the program and various data. The control unit 11 (CPU) is an example of a processor resource. The storage unit 12 may be configured with any storage device, such as a hard disk drive or a solid state drive. The storage unit 12 (as well as RAM and ROM) is an example of a memory resource. In this embodiment, the storage unit 12 stores various information such as the program 81, delivery person information 400, and store information 450. The program 81 is a program for causing the server device 1 to execute information processing (see FIG. 5 described below) related to the generation of the delivery plan 50. The program 81 includes a series of instructions for the information processing.

[0041] The communication interface 13 is configured to perform wired or wireless data communication via a network. The server device 1 may be configured with a communication interface 13, such as a wireless LAN module, a wireless LAN module, etc. In this embodiment, the server device 1 may use the communication interface 13 to perform data communication via a network with other computers (for example, a user terminal 21, an in-vehicle terminal 22, a store terminal 30, an administrator's terminal, etc.).

[0042] The drive 14 is a device for reading various information such as programs stored in the storage medium 91. At least one of the program 81, the delivery person information 400, and the store information 450 may be stored in the storage medium 91 instead of or together with the storage unit 12. The storage medium 91 is configured to store various information (such as stored programs) electrically, magnetically, optically, mechanically, or chemically so that a machine such as a computer can read the information. The server device 1 may acquire at least one of the program 81, the delivery person information 400, and the store information 450 from the storage medium 91. The storage medium 91 may be a disc-type storage medium such as a CD or a DVD, or may be a non-disk-type storage medium such as a semiconductor memory (e.g., a flash memory). The type of the drive 14 may be selected appropriately depending on the type of the storage medium 91.

[0043] Regarding the specific hardware configuration of the server device 1, components can be omitted, replaced, or added as appropriate depending on the embodiment. For example, the control unit 11 may include multiple hardware processors. The hardware processors may be a microprocessor, an FPGA (field-programmable gate array), a DSP (digital signal processor), an EC The server device 1 may be configured with an U (Electronic Control Unit), a GPU (Graphics Processing Unit), an ASIC (Application Specific Integrated Circuit), etc. The drive 14 may be omitted. The server device 1 may further include an input device and an output device. The server device 1 may be a computer designed specifically for the services provided, or may be a general-purpose server device, a general-purpose PC, etc.

[0044] [3 Example of operation] FIG. 5 is a flowchart showing an example of a processing procedure for generating a delivery plan 50 by the server device 1 according to this embodiment. The control unit 11 of the server device 1 executes instructions included in the program 81 using the CPU. As a result, the server device 1 operates as a computer capable of executing the information processing shown in FIG. 5 below. The following processing procedure is an example of an information processing method executed by a computer. However, the following processing procedure is merely an example, and each step may be changed as much as possible. Furthermore, steps in the following processing procedure may be omitted, replaced, or added as appropriate depending on the embodiment.

[0045] In step S101, the control unit 11 receives a delivery request DR from each of the multiple stores S. In one example, each store S may use the store terminal 30 to send a delivery request DR to the server device 1. The delivery request DR from each store S may be accumulated in a predetermined storage area. The control unit 11 may acquire the delivery request DR to be processed from the predetermined storage area. The predetermined storage area may be selected arbitrarily. The predetermined storage area may be, for example, RAM in the control unit 11, the storage unit 12, an external storage device, storage media, or a combination of these. The storage media may be, for example, a CD, DVD, semiconductor memory, etc. The external storage device may include, for example, a data server such as a NAS (Network Attached Storage). Upon acquiring the delivery request DR, the control unit 11 proceeds to the next step S102.

[0046] In step S102, the control unit 11 determines whether or not the delivery request DR of a first store, among the plurality of stores S, is larger than or equal to the loadable amount of one vehicle, and then determines whether or not the delivery request DR of a first store is larger than or equal to the loadable amount of one vehicle. A delivery plan 50 is generated using a dedicated delivery service that loads and delivers to only one store. In one example, the control unit 11 may generate a delivery plan 50 using a dedicated delivery service for the delivery request DR of the first store until the amount of remaining luggage falls below the load capacity of one vehicle. In another example, the control unit 11 may preferentially assign delivery tasks using a dedicated delivery service to a delivery person DP with a low delivery skill setting among multiple delivery people. Once the assignment of the dedicated delivery service is complete, the control unit 11 proceeds to the next step S103.

[0047] In step S103, the control unit 11 generates a delivery plan 50 for the remaining parcels in the delivery request DR of the first store, excluding the parcels for which a delivery plan 50 was created by a dedicated delivery service, and for the delivery request DR of the second store for which the amount of parcels to be delivered is less than the load capacity of one vehicle, by a consolidated delivery service to deliver to two or more stores. In one example, the control unit 11 may preferentially assign delivery tasks by consolidated delivery to a delivery person DP with a high delivery skill level. In another example, the control unit 11 may preferentially generate a delivery plan 50 for the delivery request DR of the second store, among the remaining part of the delivery request DR of the first store and the delivery request DR of the second store. Once the allocation of the consolidated delivery service is complete, the control unit 11 proceeds to the next step S104. Parcels not assigned in steps S102 and S103 among the received delivery requests DR may be processed in any manner.

[0048] In step S104, the control unit 11 outputs the generated delivery plan 50. The content of the information to be output and the output destination may each be determined appropriately depending on the embodiment. In one example, the control unit 11 may output the delivery plan 50 as is. The output destination may be, for example, RAM, the memory unit 12, an output device connected to the server device 1, another computer (such as an administrator's terminal), etc. In another example, the control unit 11 may send instructions to the terminal of the delivery person DP to perform delivery tasks according to the generated delivery plan 50 as an output process of the delivery plan 50. The data format of the instructions may not be particularly limited and may be determined appropriately depending on the embodiment. In yet another example, if the loading of packages and the driving of the vehicle T are automated, the control unit 11 may issue commands to the vehicle T (autonomous vehicle) to load packages and deliver the loaded packages according to the delivery plan 50 as an output process of the delivery plan 50.

[0049] When the output of the delivery plan 50 is completed, the control unit 11 ends the processing procedure for generating the delivery plan 50 according to this operation example. The control unit 11 may repeatedly execute the processing of steps S101 to S104 at any timing. In one example, the control unit 11 may repeatedly execute the processing of steps S101 to S104 periodically throughout the day. In this way, the control unit 11 may generate the delivery plan 50 in real time.

[0050] [Features] In this embodiment, the processing of step S102 preferentially plans delivery by dedicated delivery to the first store requesting more cargo than the load capacity of one vehicle. Then, the processing of step S103 plans delivery by consolidated delivery to the remaining cargo at the first store and the second store requesting less cargo than the load capacity of one vehicle. This simplifies the delivery plan 50 by prioritizing dedicated delivery, and by planning delivery by consolidated delivery for parts that are inefficient when delivered by dedicated delivery, delivery efficiency can be improved. Therefore, according to this embodiment, it is expected that an efficient delivery plan 50 that can be used on site can be generated. Note that in this embodiment, MaaS may be provided by using the server device 1.

[0051] [4 Variations] Although the embodiments of the present disclosure have been described in detail above, the above description is merely an example of the present disclosure in every respect. The processes and means described in the present disclosure can be freely combined and implemented as long as no technical contradiction occurs. Various improvements or modifications may be made to the above embodiments as appropriate.

[0052] For example, in the above embodiment, the server device 1 is an example of an information processing device. However, the form of the information processing device is not limited to this example. In another example, a terminal such as a PC, a tablet terminal, or a mobile terminal may be configured to execute the arithmetic processing of the server device 1. In this way, the terminal may be an example of an information processing device. [Explanation of symbols]

[0053] 1...server device, 11...control unit, 12...storage unit, DR...Delivery request, 50...Delivery plan 21...user terminal, 22...vehicle-mounted terminal, 30...store terminal, T...vehicle, DP...delivery person, DC...logistics center, S...store

Claims

1. Receive delivery requests from multiple stores, In response to a delivery request from a first store among the plurality of stores, the amount of cargo requested is equal to or greater than the load capacity of one vehicle, a delivery plan is generated using a dedicated vehicle that loads the load capacity of the cargo and delivers it to only that one store; and generating a delivery plan using a consolidated freight service to deliver to two or more stores for the remaining portion of the delivery requests from the first store excluding the portion for which a delivery plan has been created using the dedicated freight service and for a delivery request from a second store in which the requested amount of freight is less than the load capacity of one vehicle; a control unit configured to perform the Information processing device.

2. Generating the delivery plan for the mixed cargo service includes preferentially allocating the delivery tasks for the mixed cargo service to a delivery person having a high delivery skill level among a plurality of delivery people. The information processing device according to claim 1 .

3. Generating the delivery plan by the dedicated service includes preferentially allocating the delivery task by the dedicated service to a delivery member having a low delivery skill level among a plurality of delivery members. The information processing device according to claim 1 .

4. generating a delivery plan for the consolidated shipment includes preferentially generating a delivery plan for the delivery request of the second store among the remaining part of the delivery requests of the first store and the delivery request of the second store; The information processing device according to claim 1 .

5. 1. A computer-implemented information processing method, comprising: The information processing method includes: Receive delivery requests from multiple stores, In response to a delivery request from a first store among the plurality of stores, the amount of cargo requested is equal to or greater than the load capacity of one vehicle, a delivery plan is generated using a dedicated vehicle that loads the load capacity of the cargo and delivers it to only that one store; and generating a delivery plan using a consolidated freight service to deliver to two or more stores for the remaining portion of the delivery requests from the first store excluding the portion for which a delivery plan has been created using the dedicated freight service and for a delivery request from a second store in which the requested amount of freight is less than the load capacity of one vehicle; Including, Information processing methods.

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