JP7840201B2 - Inventory supply planning method and inventory supply planning system - Google Patents

Description

This invention relates to an inventory supply planning method and system.

Logistics centers handling multiple products and with capacity limits for storage, transportation, and CO2 emissions have traditionally managed inventory levels for all products to meet standards based on order conditions agreed upon with suppliers for each product.

The following prior art is known as background technology for this field. Patent Document 1 describes a negotiation system that generates proposed changes to order conditions that are highly beneficial to the supplier, based on the order conditions received by the supplier from the ordering party, and sends these proposed changes to the ordering party.

International Publication No. 2021/024414

Patent Document 1 does not consider the capacity of the logistics center, which is the ordering party. Therefore, if an order is placed using the proposed revised ordering conditions, it may exceed the logistics center's capacity. In particular, if inventory is optimized while maintaining the ordering conditions agreed upon by the logistics center and the supplier, it may exceed the logistics center's storage capacity and other capabilities.

However, there is a problem in that it is difficult to request significant changes to ordering conditions from suppliers in order to prevent exceeding capacity. Furthermore, even if suppliers are able to accommodate significant changes to ordering conditions and reduce the quantity per lot to satisfy storage capacity, an increase in the number of incoming shipments may lead to the volume of incoming work exceeding the logistics center's capacity, or the CO2 emissions associated with transportation and incoming operations may exceed the constraints allocated to the logistics center.

Furthermore, while it might be possible to prevent the logistics center from exceeding its capacity by requesting minor changes to ordering conditions from multiple suppliers, negotiating with each supplier for various products would require considerable effort and resources.

This invention was made in view of the above problems, and its objective is to generate proposed changes to ordering conditions that comply with the capabilities and constraints of logistics centers and other bases, and that are acceptable to suppliers.

A typical example of the invention disclosed in this invention is as follows: The present invention is an inventory supply planning method in which a computer having a computing device and a memory accessible by the computing device plans the inventory of each item to be stored at a location, wherein the computer receives a target location to be processed, and manages the initial inventory quantity by product and location for each of the multiple locations, the capacity information for location for managing the capacity upper limit index which is the upper limit of the capacity of each of the multiple locations, the unit load information set for each of the multiple locations for managing the load per unit of the item, and the target location The first step is to acquire product-specific order condition information for managing order conditions regarding the order quantity for each item, demand forecast information for managing demand forecasts for each item at the target location, and change tolerance information for managing the range of changes to the order conditions for each item. The second step is for the computer to use the initial inventory quantity for each item and location, the capacity information for each location, the unit load information, the product-specific order condition information, and the demand forecast information to generate an initial inventory supply plan for each item that is below the upper limit of the stockout rate and below the upper limit of the capacity index of the target location. The second step involves calculating a periodic inventory supply plan, and the computer calculates, based on the site-specific capacity information and the unit load information, for each item: a first capacity occupancy rate, which is the ratio of the capacity used by the item to the capacity upper limit index in the initial inventory supply plan; and a second capacity occupancy rate, which is the ratio of the capacity used by the item to the capacity upper limit index in the inventory supply plan generated by changing the ordering conditions within the permissible range of changes to the ordering conditions; and calculates the reduction amount by subtracting the second capacity occupancy rate from the first capacity occupancy rate. The process includes: a third step of calculating, for each item, a proposed change to the ordering conditions that results in a Pareto optimal reduction; a fourth step of the computer selecting from the proposed change to the ordering conditions that results in a reduction that satisfies predetermined conditions; and a fifth step of the computer modifying the product-specific ordering conditions information using the selected proposed change to the ordering conditions information for each item, and calculating a modified inventory supply plan using the initial inventory quantity for each product and location, the capacity information for each location, the unit load information, the modified product-specific ordering conditions information, and the demand forecast information .

According to one aspect of the present invention, by quantitatively evaluating the reduction in capacity utilization at logistics centers and other facilities based on proposed changes to ordering conditions for each product, negotiations with suppliers can be efficiently conducted, starting with the proposals that result in the largest reductions. As a result, ordering conditions that comply with facility capacity and are acceptable to suppliers can be determined.

Details of at least one embodiment of the subject matter disclosed herein are described in the accompanying drawings and the following description. Other features, aspects, and effects of the disclosed subject matter are revealed by the following disclosures, drawings, and claims.

This block diagram shows an embodiment of the present invention and an example of the configuration of an inventory supply planning system. This figure shows an example of the present invention and an example of product information. This figure illustrates an example of the present invention and shows an example of capability information for each location. This figure illustrates an example of the present invention and shows an example of order condition information for each product. This figure illustrates an embodiment of the present invention and shows an example of information regarding the permissible range of changes to order conditions for each product. This figure illustrates an example of daily and product-specific demand forecast information, illustrating an embodiment of the present invention. This figure illustrates an example of initial inventory information by product and location, showing an embodiment of the present invention. This figure illustrates an embodiment of the present invention and shows an example of proposed changes to order conditions. This figure illustrates an embodiment of the present invention and shows an example of negotiation result information. This figure illustrates an embodiment of the present invention and shows an example of external resource arrangement proposal information. This flowchart illustrates an embodiment of the present invention and shows an example of inventory supply planning processing. This figure illustrates an embodiment of the present invention and shows an example of a confirmation screen for proposed changes to order conditions. This flowchart illustrates an embodiment of the present invention and shows an example of the inventory supply plan calculation process. This figure shows an example of the present invention and an example of the evaluation process. This figure illustrates an embodiment of the present invention and shows an example of a confirmation screen for the inventory supply plan. This figure illustrates an embodiment of the present invention and shows another example of a confirmation screen for proposed changes to order conditions. This figure illustrates an embodiment of the present invention and shows an example of a screen for checking the status of automated negotiation. This figure shows an example of an external resource confirmation screen, illustrating an embodiment of the present invention.

Figure 1 is a block diagram showing an example of the configuration of the inventory supply planning system 1 according to an embodiment of the present invention. The inventory supply planning system 1 generates a supply plan for goods (or articles) inventory at logistics locations such as warehouses and distribution centers where goods or articles are stored.

The inventory supply planning system 1 of this embodiment of the present invention is composed of a computer having a processor (CPU) 11, a communication interface 12, an input/output interface 13, and a memory 14. The processor 11, the communication interface (indicated as "communication IF" in the figure) 12, the input/output interface (indicated as "input/output IF" in the figure) 13, and the memory 14 are connected to each other so that they can be accessed via a communication path (not shown), such as a bus.

The processor 11 is an arithmetic unit that executes programs stored in the memory 14. The various functions of the inventory supply planning system 1 are realized by the execution of various programs by the processor 11. Note that some of the processing performed by the processor 11 when executing programs may be executed by other arithmetic devices (for example, hardware FPGAs or ASICs).

Memory 14 includes a non-volatile memory element, ROM, and a volatile memory device, RAM. ROM stores immutable programs (e.g., BIOS). RAM is a high-speed, volatile memory device such as DRAM (Dynamic Random Access Memory), and temporarily stores programs executed by the processor 11 and data used during program execution (e.g., data read from storage device 2).

For example, the processor 11 functions as the order condition change proposal planning unit f1 by executing the order condition change proposal planning program. The order condition change proposal planning unit f1 formulates order condition change proposals based on various data, including order condition information for each product (or item).

Furthermore, the processor 11 functions as a negotiation unit f2 by executing a negotiation program. The negotiation unit f2 negotiates with the supplier regarding the feasibility of changing the order conditions, based on various data, including the proposed change in order conditions information o1.

Furthermore, the supplier can be an organization or entity with the authority to determine ordering conditions, such as a factory's production planning system 6 or a logistics center's outbound inventory management system 7.

Furthermore, the processor 11 functions as a screen generation unit f3 by executing a screen generation program. The screen generation unit f3 generates data for displaying on the screen so that the user can visually confirm the determined capacity utilization rate, the proposed changes to the order conditions, and the negotiation results and capacity utilization rate.

The communication interface 12 is a network interface device that controls communication with other devices via the network 9 according to a predetermined protocol.

The input/output interface 13 is connected to output devices such as a display device (not shown) and a printer (not shown), and input devices such as a keyboard (not shown), mouse (not shown), and touch panel (not shown). It is an interface that outputs the program execution results in a format visible to the user and receives input from the user.

The program executed by processor 11 is provided to the server via removable media (CD-ROM, flash memory, etc.) or a network, and stored in non-volatile memory 14 or auxiliary storage devices, which are non-temporary storage media. Therefore, the inventory supply planning system 1 should have an interface for reading data from the network or removable media.

The inventory supply planning system 1 is a computer system that operates on a single physical computer, or on multiple computers configured logically or physically. Alternatively, the inventory supply planning system 1 may operate on a virtual computer built on multiple physical computing resources.

The inventory supply planning system 1 is connected to the storage device 2. The storage device 2 has a large-capacity, non-volatile storage device, such as a magnetic storage device (HDD) or flash memory (SSD), and stores data used by the processor 11 when executing programs.

For example, the storage device 2 stores data used by the inventory supply planning system 1 for calculations, including product information i1, location-specific capacity information i2, product-specific ordering condition information i3, product-specific ordering condition change tolerance information i4, daily and product-specific demand forecast information i5, and product-specific and location-specific initial inventory information i6. Note that the "•" in "daily and product-specific" can be read as "and." The same applies to the notation of other components.

Furthermore, the storage device 2 stores the proposed order condition change information o1, negotiation result information o2, proposed external resource arrangement information o3, and inventory supply plan o4, which are output by the inventory supply planning system 1 as a result of its calculations. The inventory supply plan o4 includes daily, product-specific, and route-specific transport volume information o41, daily, vehicle-type-specific, and route-specific transport volume information o42, and daily, product-specific, and location-specific inbound/outbound and inventory volume information o43. Details of this information will be described later. The storage device 2 may also store programs executed by the processor 11.

In the configuration shown in Figure 1, a storage device 2 is provided separately from the inventory supply planning system 1. However, an auxiliary storage device, which is a non-volatile storage device for storing data, may be provided within the inventory supply planning system 1.

The inventory supply planning system 1 may be connected to other systems (for example, customer POS system 3, order management system 4, external resource management system 5, production planning system 6, outbound inventory management system 7, and transportation management system 8) via the communication interface 12 and network 9.

The customer POS system 3 is a system for managing product sales at retail stores and is also used by retail stores to order products. The customer POS system 3 is operated, for example, by the person ordering the products.

The Order Management System 4 is a system for managing orders by supplier and by product. It is used to agree on ordering conditions with suppliers and to place orders for goods from locations to suppliers. The Order Management System 4 is operated, for example, by the person placing the order for the goods.

The External Resource Management System 5 is a system for arranging and managing external resources such as chartered vehicles for transportation, external warehouses for storage, and workers for operations. The External Resource Management System 5 may be operated by, for example, the manager of the logistics center, or by an organization outside the logistics center.

The production planning system 6 is a system for planning the production of goods at various locations such as factories. The production planning system 6 is operated, for example, by the goods supplier. The outbound inventory management system 7 is a system for managing the outbound shipment of goods at various locations such as factories and warehouses. The outbound inventory management system 7 can be operated, for example, by the supplier or logistics center. The transportation management system 8 is a system for transportation companies to manage the operation of transportation methods. The transportation management system 8 can be operated, for example, by the supplier or logistics center in addition to the transportation company.

For example, the inventory supply planning system 1 aggregates demand forecast and order information for products transmitted from the customer's POS system 3 to generate the requested arrival date and predicted quantity for each product. Then, based on the predicted quantity, product-specific order condition information i3, and product-specific/location-specific initial inventory information i6, the inventory supply planning system 1 devises and outputs an inventory supply plan o4 that minimizes the cost of adhering daily to the capacity set in location-specific capacity information i2.

If the inventory supply planning system 1's output inventory supply plan exceeds the logistics center's capacity, it automatically negotiates changes to the ordering conditions in the ordering management system 4 based on the proposed changes to the ordering conditions information o1. The inventory supply planning system 1 can output negotiation result information o2, which is the result of the automatic negotiation, or, if the capacity is still exceeded after negotiation, it can output proposed external resource arrangement information o3.

Based on the external resource arrangement proposal information o3 output from the inventory supply planning system 1, the external resource management system 5 can arrange the external resources (transportation, storage, labor) as described above.

Based on the negotiation result information o2 output from the inventory supply planning system 1, the production planning system 6 can formulate or modify the production plan, the outbound inventory management system 7 can generate or modify outbound inventory instructions, and the transportation management system 8 can generate or modify dispatch instructions.

Figure 2 shows an example of product information i1. Product information i1 includes at least the product name 111, unit volume 112, unit CO2 emission 113, and stockout rate limit 114 in a single record.

Product name 111 is a data item that stores the name (or identifier) of the product. Unit volume 112 stores the volume (or capacity) per unit quantity of the product, which is necessary to calculate the volume occupied by the product relative to the capacity of the facility. Unit CO2 emissions 113 stores the amount of CO2 emissions per unit quantity of the product during logistics operations from receiving to shipping.

The "Out-of-Stock Rate Limit 114" stores the upper limit of the acceptable out-of-stock rate for a product. The out-of-stock rate represents the ratio of the quantity lacking to the pre-set inventory level for each product. Furthermore, the values for each item in product information i1 are pre-set.

Furthermore, product information i1 may include data items for indicator values such as "unit weight," which is the weight per unit quantity, although these are not shown in the illustration. In this embodiment, the unit quantity is referred to as pcs (pieces), but it could also be a case, pallet, or other unit. Also, in this embodiment, the unit of volume is tai, but other units such as liters could be used.

Furthermore, the unit volume 112, the unit CO2 emission 113, and the stockout rate limit 114 represent information about the load on the base, and since they indicate the load per unit that has been set in advance, they can be considered as unit loads, and product information i1 can be treated as unit load information.

Figure 3 shows an example of site-specific capacity information i2. Site-specific capacity information i2 includes at least the site name 121, address 122, inventory storage volume limit 123, CO2 emission limit 124, and receiving work volume limit 125 in a single record.

Location Name 121 stores the name of the location (logistics center), and Address 122 stores the address of the location. Inventory Storage Volume Limit 123 stores the maximum volume of goods that can be stored at that location.

The CO2 emission limit 124 stores the annual CO2 emissions allocated to the location. The receiving work volume limit 125 stores the maximum daily handling volume of goods set for the location. It may also be set for a combination of location name and date (not shown). Note that the values for each item in the location-specific capacity information i2 are pre-set.

Furthermore, the base-specific capacity information i2 may include data items indicating upper limits on transport capacity, such as "maximum transport volume" and "maximum number of transported vehicles," for each receiving route from the supplier. This data may also be set for combinations of receiving routes and dates (not shown). It may also include data items representing the geographical location of the base, such as "address" and "latitude/longitude" (not shown).

Furthermore, in terms of the facility's capabilities, it's possible to set limits on the area available for storing goods, restrictions on CO2 emissions during transportation such as receiving and shipping goods, and limits on costs and the volume of receiving operations.

Figure 4 shows an example of product-specific order condition information i3. Product-specific order condition information i3 includes at least the product name 131, the supplier location name 132, the order lot size 133, and the minimum order quantity 134 in a single record.

Product Name 131 stores the name of the product. Supplier Location Name 132 stores the name of the location from which the product is shipped. Order Lot Size 133 stores the quantity of one lot, which is the order unit for the product. Minimum Order Quantity 134 stores the minimum quantity required when ordering the product. Note that the values for each item in Product-Specific Order Condition Information i3 are pre-set.

Product-specific ordering condition information i3 may also include data items for setting ordering conditions when placing orders from a location to a supplier, such as lead time, price, ordering cycle, ordering method, reorder point (or ordering timing), and standard inventory level, although these are not shown in the illustration.

Figure 5 shows an example of the product-specific order condition change tolerance information i4. The product-specific order condition change tolerance information i4 includes at least the product name 141, the lower limit 142 and upper limit 143 of the order lot size change tolerance range, and the lower limit 144 and upper limit 145 of the minimum order quantity change tolerance range in a single record. The values for each item in the change tolerance information i4 are pre-set.

Furthermore, the above acceptable range of change may be defined for each order condition as shown in the product-specific order condition information i3 in Figure 4, with upper and lower limits set accordingly. These upper and lower limits may be set as ratios or percentages, or as absolute quantities.

Figure 6 shows an example of daily and product-specific demand forecast information i5. The daily and product-specific demand forecast information i5 includes at least the order ID 161, the arrival request date 162, the product name 163, the destination location name 164, the forecasted quantity 165, and the variance of the demand forecast error 166 in a single record.

Order ID 161 stores the identifier of the forecast information. Arrival Request Date 162 stores the date the goods should arrive at the location. Product Name 163 stores the product name of the item subject to demand forecasting. Delivery Location Name 164 stores the name of the location where the goods should be delivered. Forecast Demand Quantity 165 stores the forecasted demand quantity of the goods. Demand Forecast Error Variance 166 stores the result of calculating the error variance.

Furthermore, the daily and product-specific demand forecast information i5 may include data items such as forecast dates, in addition to the items mentioned above, although these are not shown in the diagram. Also, instead of daily demand forecasts as in this embodiment, monthly or other monthly demand forecasts may be used.

Figure 7 shows an example of initial inventory information i6 by product and location. The initial inventory information i6 by product and location includes at least the product name 167, location name 168, and inventory quantity 169 in a single record. Product name 167 stores the name of the product stored at the location. Location name 168 stores the name or identifier of the location. Inventory quantity 169 stores the initial inventory quantity of the product. The values of each item in the initial inventory information i6 by product and location are pre-set. The initial inventory quantity can be set for each combination of product and location in the initial inventory information i6 by product and location.

The initial inventory information i6 by product and location may also include unit price information by product and location to calculate costs incurred at each location (not shown). This may include storage costs incurred when storing goods at that location, and inbound/outbound work costs (not shown) incurred when goods are received or shipped at that location. Inbound and outbound work costs may also be defined separately.

Furthermore, to calculate the costs incurred during transportation, unit price information may be set for each receiving route and transportation type (not shown). Transportation types may be set for combinations of vehicle type, container size, and transportation methods such as rail, rail, and ship.

Furthermore, the initial inventory information i6 by product and location may also represent the current inventory levels for each product and location, and is updated at predetermined intervals (for example, daily).

Figure 8 shows an example of the proposed order condition change information o1 output by the inventory supply planning system 1. The proposed order condition change information o1 includes the proposed condition change #171, product name 172, order lot size 173, minimum order quantity 174, change in the maximum storage capacity occupancy rate 175, and change in the maximum receiving operation capacity occupancy rate 176, all in a single record.

Condition Change Proposal #171 stores the identifier of the condition change proposal assigned by the inventory supply planning system 1. Product Name 172 stores the name (or identifier) of the product. Order Lot Size 173 stores the quantity of the product per lot under the modified ordering conditions. Minimum Order Quantity 174 stores the lower limit of the quantity of the product that can be ordered in a single order under the modified ordering conditions.

The change in the maximum storage capacity occupancy rate, 175, stores the change in the occupancy rate of the proposed order condition change relative to the maximum storage capacity that changes as a result of the proposed change (revised inventory supply plan). The change is calculated by subtracting the capacity occupancy rate of the revised inventory supply plan from the capacity occupancy rate of the initial inventory supply plan. For example, if the maximum inventory storage volume 123 is 100,000 cubic feet, and the unit volume of a product is 1.0 cubic foot/pcs, a reduction of 10,000 units in inventory would result in a reduction rate of -10 pt (%).

Furthermore, the change in the maximum value of the receiving operation capacity occupancy rate, 176, stores the change in the maximum value of the receiving operation capacity that changes as a result of the proposed modification.

In this embodiment, the order condition change proposal planning unit f1 calculates the ratio of each capacity used by each product to the upper capacity limit (capacity limit index) set in the base-specific capacity information i2, as the capacity utilization rate (or maximum capacity utilization rate).

The order condition change proposal information o1 stores zero or more proposed changes for each product that reduce capacity utilization while maintaining the acceptable range of changes to the order conditions. Each proposed change includes a suggested setting value for the order condition and the change in capacity utilization when an order is placed using that setting value.

In the illustrated example, the original ordering conditions for "Product A" are as shown in Figure 4: order lot size 133 = "1000" and minimum order quantity 134 = "2000". However, in the case of proposed change #171 = "1", the order lot size 173 is reduced to "500" and the minimum order quantity 174 is reduced to "1000".

Furthermore, in the proposed order condition change information o1, if this proposed condition change #171 = "1" is implemented, the change in the maximum value of the storage stress occupancy rate 175 = "-10 pt (%)" will be reduced, thus decreasing the occupancy rate relative to storage capacity. However, since the order lot size 173 decreases to "500" and the minimum order quantity 174 also decreases to "1000", the receiving operations at the base will increase. Therefore, the change in the maximum value of the receiving operation capacity occupancy rate 176 is shown to increase to "+3 pt".

Figure 9 shows an example of negotiation result information o2 output by the inventory supply planning system 1. Negotiation result information o2 stores the results of negotiations between the inventory supply planning system 1 and the production planning system 6, the outbound management system 7, or the transportation management system 8.

The negotiation result information o2 includes the negotiation order #181, the proposed change in conditions #182, the change in the maximum capacity utilization rate (storage 183, receiving operations 184), the maximum capacity utilization rate under the order conditions at the start of negotiations (storage 185, receiving operations 186), and the negotiation status 187, all in a single record.

Negotiation Order #181 stores the order of negotiations being conducted by the Inventory Supply Planning System 1. Condition Change Proposal #182 stores the value of Condition Change Proposal #171 from Order Condition Change Proposal Information o1.

The change in the maximum capacity utilization rate, specifically storage (183), stores the change in the maximum storage volume calculated from the negotiation results. The change in storage volume is expressed as a percentage of the ratio of storage volume (in units) to the inventory storage volume limit (123) in the base-specific capacity information i2.

The change in the maximum capacity utilization rate for receiving work 184 stores the change in the maximum receiving work volume calculated from the negotiation results. The change in receiving work volume is expressed as a percentage of the ratio of the work volume (pcs/day) to the upper limit of receiving work volume 125 in the capacity information i2 for each location.

The maximum capacity utilization rate under the order conditions at the start of negotiations, specifically storage 185, stores the maximum capacity utilization rate of storage volume calculated from the order quantity at the start of negotiations. The maximum capacity utilization rate of storage volume is expressed as a percentage of the ratio of storage volume (in units of 123) to the inventory storage volume limit 123 in the site-specific capacity information i2.

The maximum capacity utilization rate for receiving work 186, based on the order conditions at the start of negotiations, stores the maximum capacity utilization rate of receiving work volume calculated from the order volume at the start of negotiations. The capacity utilization rate of receiving work volume is expressed as a percentage of the ratio of work volume (pcs/day) to the upper limit of receiving work volume 125 in the capacity information i2 for each location. The negotiation status 187 stores the result or progress of the negotiations.

The negotiation result information o2 stores the change in the capacity occupancy rate relative to the base-specific capacity information i2, both at the start of negotiations and after the negotiations, for each proposed change in conditions #182.

Figure 10 shows an example of external resource procurement proposal information o3 output by the inventory supply planning system 1. External resource procurement proposal information o3 holds procurement proposals for using external resources when resources at the target location are insufficient.

External resource procurement proposal information o3 includes the capability type 191, resource type 192, required quantity 193, required duration 194, procurement proposal 195, total cost increase 196, procurement negotiation order #197, and procurement negotiation status 197 in a single record.

Capacity type 191 stores the category of the insufficient resource. In the example shown, it represents "Storage," but other capacities such as "Transportation," "Receiving," and "Outbound" can also be stored. Resource type 192 stores the type of resource that is insufficient. In the example shown, it represents "External Warehouse," but other resource types such as "Vehicles" and "Workers" can also be stored.

Required Quantity 193 stores the quantity required for Resource Type 192. Required Period 194 stores the start and end dates. Proposed Arrangement 195 stores the name (or identifier) of the external resource's user. Total Cost Increase 196 stores the cost increase when using the external resource. Arrangement Negotiation Order #197 stores the order in which the negotiation for this record is performed. Arrangement Negotiation Status 198 stores the negotiation result or status of the external resource negotiation.

Although not illustrated, the inventory supply plan o4 includes information such as product name, order date, scheduled arrival date and time, quantity on each date, and supplier. It can also include daily, product-specific, and route-specific transport volume information o41, daily, vehicle-specific, and route-specific transport volume information o42, and daily, product-specific, and location-specific inbound/outbound and inventory volume information o43.

Figure 11 is a flowchart S1 showing an example of the inventory supply planning process performed by the inventory supply planning system 1. Below, we will first explain the overall overview of flowchart S1, and then describe the process for each step. This process is executed at predetermined intervals (for example, daily) or according to instructions from administrators or users.

First, the inventory supply planning system 1 receives the target locations for processing via the order condition change proposal planning unit f1 and obtains the following input data from the storage device 2: product information i1, location-specific capacity information i2, product-specific order condition information i3, product-specific order condition change tolerance information i4, daily/product-specific demand forecast information i5, and product/location-specific initial inventory information i6 (S10).

Next, the order condition change proposal planning unit f1 calculates an inventory supply plan o4 that satisfies the stockout rate limit 114 and the capacity of the processing site (inventory storage volume limit 123, CO2 emission limit 124, receiving work volume limit 125) based on the product-specific order condition information i3 agreed upon with the supplier and inventory supply planning system 1 shown in Figure 4 (S11).

In other words, the order condition change proposal planning unit f1 calculates one or more inventory supply plans that satisfy the processing location capacity information i2 for each product's current inventory level, based on the initial inventory information i6 for each product and location, the stockout rate limit 114 of the product information i1, and the order conditions. If there is no solution that satisfies all of the location capacity information i2, the order condition change proposal planning unit f1 can designate an inventory supply plan that satisfies one of the following: the inventory storage volume limit 123, the CO2 emission limit 124, and the receiving work volume limit 125, as the Pareto optimal inventory supply plan o4.

Furthermore, the generation of the inventory supply plan o4 calculated by the order condition change proposal planning unit f1 can utilize well-known or publicly recognized methods. Also, if external resources from the base are available, the order condition change proposal planning unit f1 does not need to meet the capacity of the target base (inventory storage volume limit 123, CO2 emission limit 124, receiving work volume limit 125). In this case, the order condition change proposal planning unit f1 only needs to calculate one or more inventory supply plans based on the stockout rate limit 114 and the order conditions.

Next, the order condition change proposal planning unit f1 calculates a proposed order condition change for each product name 111 registered in product information i1, based on the input data from product information i1 to product-specific/location-specific initial inventory information i6. Within the permissible range of order condition changes (i4) for each product name 111, the unit calculates a proposed order condition change that results in a Pareto optimal reduction in the location's capacity utilization rate (change amount 175 or change amount 176), and stores it in the proposed order condition change information o1 (S12). The inventory supply plan formulated with the Pareto optimal proposed order condition change is designated as the modified inventory supply plan. Furthermore, the reduction in capacity utilization rate for each product serves as an order condition determination index when deciding on the proposed order condition change.

The order condition change proposal planning unit f1 can, for example, calculate multiple condition change proposals (i.e., revised inventory supply plans) for a single product within the acceptable range of changes set in the product-specific order condition change tolerance information i4. In other words, the order condition change proposal planning unit f1 can search for product-specific order condition change proposals that satisfy the upper limit of the location-specific capacity information i2.

Furthermore, Pareto optimization refers to a state in the revised inventory supply plan where the capacity utilization rate of goods is efficiently allocated to the capacity information i2 for each location.

Next, the negotiation unit f2 repeats the process from step S13 to step S19 until the predetermined termination conditions are met.

First, the negotiating department f2, in step S14, selects a revised inventory supply plan (revised inventory supply plan) that, based on the product-specific ordering condition information i3 agreed upon with the supplier, allows the change in ordering conditions to comply with the capacity of the site (site-specific capacity information i2), and maximizes the reduction in the capacity occupancy rate for capacity exceeding site-specific capacity information i2.

Negotiation Department f2 selects one proposed change in order conditions #171 from the unprocessed proposed changes in order conditions information o1 that satisfies the above selection criteria. Here, Negotiation Department f2 sorts the proposed changes in order conditions information o1 by product in descending order of the reduction amount (change amount 175 or 176), and selects the proposed change in order of the reduction amount for each product.

Next, the negotiation unit f2 negotiates the proposed order condition changes selected in step S14 with each supplier for each product (S15). The negotiation unit f2 transmits the selected order condition changes to the supplier's production planning system 6 or inventory management system 7 to inquire whether the changes will be accepted. The negotiation unit f2 receives the acceptance or rejection response from the supplier as the negotiation result.

Negotiations regarding proposed changes to order terms with suppliers may be conducted automatically between computers such as the inventory supply planning system 1 and the production planning system 6, but human intervention by administrators or operators is also permitted. While the automated negotiation of proposed changes to order terms between computers is envisioned to involve the supplier's computer determining whether to accept the proposed changes sent by the inventory supply planning system 1, automated negotiations using machine learning models may also be employed.

In step S16, the negotiation unit f2 determines whether to negotiate the proposed changes to the order conditions. If the negotiation is successful, the process proceeds to step S17; otherwise, it proceeds to step S19 and repeats the process from step S13. In other words, the negotiation unit f2 negotiates the proposed changes to the order conditions in order of the largest reduction amount, repeating the process until an agreement is reached.

In step S17, the negotiation unit f2 updates the proposed capacity occupancy rate based on the changes in occupancy rates calculated in step S11 (a change of 175 in the maximum storage capacity occupancy rate and a change of 176 in the maximum receiving capacity occupancy rate) for the proposed order condition changes that were agreed upon in step S15. Note that the capacity information i2 for each location may also contain capacity occupancy rates for the proposed condition changes (not shown), and the negotiation unit f2 may update the capacity occupancy rate according to the change of 176.

Next, the negotiation unit f2 determines whether the pre-set termination conditions are met. If the termination conditions are met, the loop process ends and proceeds to step S20. If the termination conditions are not met, it returns to step S13 and executes the above loop process with the new proposed order condition changes.

Furthermore, the predetermined termination conditions for the loop processing in steps S13 to S19 can be, for example, when the order condition changes for all products subject to processing satisfy the location-specific capacity information i2, when all negotiations to be carried out in step S15 are completed, or when the number of loop processing iterations exceeds a predetermined number.

Next, the negotiation unit f2 modifies the product-specific order condition information i3 corresponding to all the proposed order condition changes that were agreed upon in the loop of steps S13 to S19 (S20).

In step S21, the negotiation unit f2 determines whether the inventory supply plan o4 generated using the product-specific order condition information i3, to which the above-mentioned order condition changes have been applied, meets the capacity limit of the base. The negotiation unit f2 then determines whether the generated inventory supply plan o4 is within the capacity limit of the base-specific capacity information i2.

Negotiation unit f2 determines that the capacity limit is met if the inventory supply plan o4 is within the capacity of the site-specific capacity information i2, and terminates processing. On the other hand, if the inventory supply plan o4 exceeds the capacity limit, negotiating unit f2 calculates the required amount of external resources to compensate for the excess, and arranges for those external resources in step S22, in order to utilize external resources other than those of the site being processed (S22).

Through the above process, the inventory supply planning system 1 can generate proposed changes to ordering conditions that comply with the capacity of logistics centers and other locations, and that are acceptable to the supplier.

Next, the details of the process performed in step S10 above will be explained. The screen generation unit f3 generates display data for the input/confirmation screen from the input data received by the order condition change proposal unit f1, and the display data may be output to an external computer via the input/output interface 13 and displayed on a display device (not shown).

Figure 12 shows an example of the input and confirmation screen d1 for formulating proposed changes to order conditions. The data displayed on the input and confirmation screen d1 is generated by the screen generation unit f3. The input and confirmation screen d1 includes a region d11 displaying the contents of the region-specific capacity information i2, a region d12 displaying the contents of the product-specific order condition information i3, an edit button d13 for the input data, and an execution button d14 for formulating the proposed changes to the conditions.

On the input/confirmation screen d1, you can edit the contents of the location-specific capacity information i2 and the product-specific order condition information i3. You can edit or update the input data by operating the input data edit button d13.

Users and administrators of the inventory supply planning system 1 can start the process from step S10 onwards, as shown in Figure 11, by operating the execution button d14 for drafting the proposed condition change after editing or confirming the input data.

Next, we will explain the details of the process performed in step S11. In step S11, shown in Figure 2, the order condition change proposal unit f1 outputs an inventory supply plan o4 that satisfies the stockout rate limit 114 and the capacity of the processing location, based on the product-specific order condition information i3 agreed upon with the supplier and the inventory supply planning system 1.

The Order Condition Change Planning Unit f1, using the products registered in Product Information i1, and based on the location-specific capacity information i2, the product-specific order condition information i3 agreed upon with the supplier, the daily and product-specific demand forecast information i5, and the product-specific and location-specific initial inventory information i6, formulates an inventory supply plan o4 that satisfies the stockout rate limit and the capacity of the target location under the agreed-upon order conditions. This inventory supply plan is calculated using the process shown in flowchart S2 in Figure 13.

First, in step S21, the order condition change proposal planning unit f1, in accordance with the product-specific order condition information i3 agreed upon with the supplier, and based on the product-specific and location-specific initial inventory information i6, formulates an inventory supply plan o4, as described below, consisting of daily, product-specific, and route-specific transport volume information o41, daily, vehicle type-specific, and route-specific transport volume information o42, and daily, product-specific, and location-specific inbound/outbound and inventory volume information o43, to satisfy the capacity limits set in the location-specific capacity information i2.

One method for formulating the inventory supply plan o4 is to have the order condition change proposal planning unit f1 automatically generate all possible combinations of transport volume, transport volume, inbound/outbound volume, inventory volume, and stockout volume, thereby generating all possible inventory supply plans o4.

The order condition change proposal planning unit f1 may then explore all possible inventory supply plans o4 generated by repeating steps S21 to S26 for each plan, and determine the inventory supply plan o4 that satisfies the stockout rate limit 114 and has the best KPI (Key Performance Indicator). Here, the KPI may include multiple factors such as total cost, CO2 emissions, sales, cash flow, and inventory level.

Another method for formulating inventory supply plan o4 is to allocate transportation to the available capacity, starting with the order with the latest requested arrival date (or expected arrival date), up to the maximum transportation volume and number of vehicles, to meet the requested quantity for that order. Any transportation exceeding the capacity is then allocated by bringing forward the delivery date, thereby determining the daily, product-specific, and route-specific transportation volumes.

Given the departure date t, route p, vehicle type v, and goods i, the number of vehicles transported (vcnt(t, p, v)) can be calculated based on the transport volume trans(t, p, v, i) using the following formula. The elements and formula for this calculation are shown below.

·set:
• Dates covered by the plan: 0, 1, ~ T
• Collection of products: I
• Set of paths: P
- Base gathering: W
- Set of routes to reach base w: Pw
・Constant: Hereinafter, t∈T
• Unit volume of product i: ItemUnitVol(i)
• Maximum load capacity for vehicle type v: VehicleVolUB(v)
The formula for calculating the number of transported vehicles, where vcnt(t, p, v), is given below.

The above calculation only considered volume as the maximum load capacity. However, if weight is also considered, for example, the larger of the number of transport units calculated based on the maximum load volume or the number of transport units calculated based on the maximum load weight should be used.

Furthermore, based on the above transportation volume, daily, location-specific, and product-specific inbound volumes can be calculated by summing the transportation volumes for the entire route from upstream, for the same arrival date and product.

Daily, location-specific, and product-specific incoming inventory volumes can be calculated by summing the total transport volume from the entire upstream route for the same product on the same arrival date. Daily, location-specific, and product-specific discard volumes can be calculated by summing the inventory volume on that day that exceeds the maximum storage period from the start date of storage, broken down by location and product.

For a given date t, location w, and product i, the daily, location-specific, and product-specific inventory quantity stock(t, w, i) can be calculated using the incoming quantity in(t, w, i) and outgoing quantity out(t, w, i), calculated using the method described above, as follows:

·constant:
• Initial stock quantity: InitStock(w,i)
The formula for calculating the inventory quantity stock(t, w, i) is shown below.

When defining inventory storage volume limits, inbound quantity limits, and outbound quantity limits in inventory capacity information i2 by location, any amounts exceeding these limits should be adjusted so that the inbound or outbound quantities fall below the limits, and the excess amount should be recorded as a stockout.

The daily, location-specific, and product-specific stockout quantity, `shortage(t, w, i)`, can be calculated using the following formula, where `requestQty(t, p, i)` (p ∈ P) is the quantity of requests from downstream to the set of downstream routes P of location w.

The formula for calculating the amount of goods requested from downstream to base w, requestQty(t, w, i), is shown below.

The formula for calculating the stock shortage (shortage(t, w, i)) can be expressed as follows:

Next, we will explain the details of step S22. In step S22, the order condition change proposal planning unit f1 evaluates the capacity utilization rate of the base, KPIs such as total cost, CO2 emissions, sales, cash flow, and inventory level, and the stockout rate, assuming that the inventory supply plan o4 formulated in step S21 is implemented. Figure 14 shows a flowchart S3 illustrating the details of the process performed in step S22.

First, in step S31, the order condition change proposal planning unit f1 generates estimated daily, product-specific, and route-specific demand quantities based on the predicted demand quantity 165 in the product-specific daily and product-specific demand forecast information i5 and the variance of the demand forecast error 166. The estimated demand quantities can be generated by adding random noise, etc., generated based on the demand forecast error variance 166, to the predicted demand quantity 165.

Next, in step S32, the order condition change proposal planning unit f1 simulates the transport volume, number of transported vehicles, inbound/outbound quantities, inventory quantity, stockout quantity, and outbound order quantities for each day from the first day of the planning period until the last day, assuming that the inventory supply plan o4, formulated in step S31 based on the daily/product-specific demand forecast information i5, is executed, and that the actual demand is the assumed demand quantity generated in step S31, resulting in a difference between forecast and actual demand.

For example, if demand falls below expectations on a given day, a portion of the inventory prepared for that demand becomes surplus and is rolled over to the next day. If demand rises above expectations on a given day, exceeding inventory, a shortage occurs, inventory becomes zero, and this is also rolled over to the next day. By repeating this process until the final day, it's possible to simulate the changes in each quantity, taking into account errors in demand forecasting.

Finally, in step S33, the order condition change proposal planning unit f1 evaluates the capacity utilization rate and KPIs such as total cost, as well as the stockout rate, based on the transportation volume, number of vehicles transported, inbound/outbound volume, inventory volume, stockout volume, and outbound request volume obtained from the simulation results, using the following formula.

·constant:
Storage capacity upper limit StockCapUpBound(w),
CO2 emission capacity upper limit CO2EmissionCapUpBound(w),
Unit storage load StockUnitLoad(w, i),
CO2 Emission Unit Load (Storage) CO2EmissionUnitLoadSt(w,i)
CO2 Emission Unit Load In (w, i)
CO2 Emission Unit Load Out (w, i),
Unit CO2 Emission Load (Transport) CO2EmissionUnitLoadTrans(p,v)
CO2 Emission Unit Load Disposal (w, i)
Transportation cost (transUnitCost(t, p, v))
Storage unit cost StockUnitCost(w, i),
Disposal unit cost (w, i),
Inbound work unit cost InputUnitCost(w, i),
Outbound work unit cost (w, i),
Unit Book Value (w, i)

·variable:
Storage capacity occupancy occupiedVolCapRatio,
CO2 emission capacity occupiedCO2CapRatio,
Total cost totCost,
Transportation cost transCost,
Storage costs,
Disposal cost,
Inbound processing cost, inputCost,
Outbound shipping cost,
Average inventory value aveInventory,
Shortage Rate

The formula for calculating the occupiedVolCapRatio(w) using the above constants and variables can be expressed as follows:

The following is an example of a KPI calculation formula that evaluates performance using total cost, average inventory value, and stockout rate.

The formula for calculating the total cost (totCost) can be expressed as follows:

The average inventory value (aveInventory) can be expressed by the following formula:

The formula for calculating the stockout rate (shortageRate) can be expressed as follows:

The above examples use storage and CO2 emissions as capacity for evaluating KPIs at a facility, but KPIs can also be evaluated for transportation capacity or inbound/outbound operations capacity. The above examples use total cost and average inventory value as KPIs, but inventory volume, CO2 emissions, sales volume, or cash flow could also be used. The above examples assume transportation costs are added per vehicle, but a variable cost term that is continuously added in proportion to the volume of transportation may also be added.

Next, returning to Figure 13, we will explain the details of steps S23 to S25. First, in step S23, the order condition change proposal planning unit f1 determines whether the shortfall rate calculated in step S22 satisfies the upper limit of the shortfall rate 114. If it satisfies the upper limit, it proceeds to the next step S24; if it exceeds the upper limit, it proceeds to step S26.

Next, in step S24, the order condition change proposal planning unit f1 determines whether the excess capacity (difference from the upper limit of the site-specific capacity information i2) for one or more capacity indicators (storage, CO2 emissions, etc.) is zero or smaller than the provisional solution. If it is smaller, the unit proceeds to step S25; otherwise, it proceeds to step S26.

Next, in step S26, the order condition change proposal planning unit f1 saves the inventory supply plan calculated in step S21 as a provisional solution that satisfies the stockout rate limit 114 and has zero or minimal capacity excess in a predetermined area of memory 14.

In the example in Figure 13, the inventory supply plan calculated by the order condition change proposal planning unit f1 is saved as a provisional solution only when the stockout rate limit 114 is met and the excess capacity is zero or smaller than the provisional solution. However, all other cases may also be saved as relaxed condition proposals or next-best plan proposals. Furthermore, if the excess capacity is the same as the provisional solution, the solution with the best performance in any of the KPI indicators may be saved as the Pareto-optimal provisional solution.

In step S26, the order condition change proposal planning unit f1 determines whether the predetermined termination conditions are met. These predetermined termination conditions include pre-set limits on the number of repetitions of the process from steps S21 to S26 and the lower limit on the improvement rate of the capacity overrun. If these limits are met, the unit determines that the termination conditions are met and proceeds to step S27.

If the termination conditions are not met, the process from steps S21 to S26 above is repeated. In that case, in step S21, the order condition change proposal unit f1 should, for example, in the case of a full search, generate an inventory supply plan for the unexplored combinations of transport volume, transport volume, inbound/outbound volume, inventory volume, waste volume, and stockout volume. Alternatively, the order condition change proposal unit f1 may increase or decrease some of the quantities in the provisional inventory supply plan to generate a new inventory supply plan.

Next, the details of step S27 will be explained. The order condition change proposal planning unit f1 saves the multiple Pareto optimal provisional solutions obtained in the above loop processing as an inventory supply plan o4 that satisfies the capacity of the site-specific capacity information i2 under the order conditions agreed upon with the supplier. The screen generation unit f3 generates display data for a confirmation screen of the change proposal results from the saved inventory supply plan o4. The generated display data is output from the input/output interface 13 and displayed on a display device (not shown) or the like.

Figure 15 shows an example of the display of the confirmation screen d2 of the inventory supply plan. The confirmation screen d2 includes areas for capacity compliance status d21, time-series graph d22, and KPI graph d23.

The capacity compliance status d21 displays a graph of the Pareto-optimal plan that was devised. This graph shows the relationship between storage capacity and receiving capacity, with receiving workload on the horizontal axis and storage volume on the vertical axis. The solid line graph in the illustration shows an example of an inventory supply plan where receiving workload and storage volume are Pareto-optimal. The illustration shows an example where storage volume is maximized in inventory supply plan "Plan 1," and receiving workload is maximized in inventory supply plan "Plan 2." Note that "Plan 1" is inventory supply plan o4 that minimizes total cost, and "Plan 2" is inventory supply plan o4 that minimizes total cost. The total cost is the predicted cost when the above inventory supply plan is implemented.

Capacity compliance status d21 can be composed of graphs showing the correlation between capacity at each location, including storage volume, receiving volume, CO2 emissions, and costs.

Time-series graph d22 shows an example composed of graphs for storage volume and date, and graphs for receiving work volume and date. The graphs illustrate an example where, under "Plan 1," storage volume exceeds storage capacity on certain days. Furthermore, under "Plan 2," receiving work volume exceeds receiving capacity on certain days.

KPI graph d23 shows examples of radar charts for "Plan 1" and "Plan 2" of the inventory supply plan o4. The radar charts are examples composed of indicators related to CO2 emissions, inventory value, cash flow, and total cost. Note that the radar charts are not limited to those shown; indicators that evaluate the capacity of the site can be used.

Furthermore, the screen generation unit f3 may output an inventory supply plan in which the stockout rate satisfies the upper limit of 114, and at least one of the KPIs (Key Performance Indicators) such as total cost, CO2 emissions, inventory value, inventory quantity, and cash flow is optimal. The conditions for optimal KPIs are that total cost, CO2 emissions, inventory value, and inventory quantity are at their minimum values, while cash flow is at its maximum value. Also, as mentioned above, if plans other than the Pareto optimal plan have been saved, other plans may be displayed.

Returning to Figure 11, let's explain the details of step S12. The order condition change proposal unit f1 calculates, for each product, a proposed change that results in a Pareto-optimal reduction in capacity utilization, within the range of the permissible range information i4 for changes to the order conditions for each product.

The process in step S12 is achieved by the order condition change proposal planning unit f1, while varying the order conditions agreed upon with the customer (supplier) within the range of the permissible change information i4, and using the same method as in step S11, following the flowchart S2 in Figure 13, formulating an inventory supply plan that satisfies the capacity of the site-specific capacity information i2 under the order conditions. The capacity utilization rate, KPIs, and stockout rate of the formulated inventory supply plan are then evaluated, and the evaluated plan is saved to the inventory supply plan o4.

The screen generation unit f3 generates display data for the confirmation screen d3 of the proposed changes to the order conditions based on the saved inventory supply plan o4, and can output it from the input/output interface 13 for display on a display device or the like.

Figure 16 shows an example of the display of the confirmation screen d3 for the proposed changes to the order conditions. The confirmation screen d3 includes the Pareto optimization results d31, a time-series graph d32, a list of proposed changes d325, an edit button d33 for drafting the proposed changes, and a negotiation start button d34.

The Pareto optimization result d31 displays a graph of the devised Pareto-optimal inventory supply plan o4. This graph shows an example of displaying the Pareto optimality for "Condition 1," "Condition 2," and "Condition 3," with the horizontal axis representing receiving work volume and the vertical axis representing storage volume.

Time-series graph d32 shows the relationship between storage volume and date, illustrating the relationship between the change in storage volume for each day under conditions 1 to 3 and the maximum storage volume. Compared to before the change in ordering conditions, the proposed changes (condition 1) to (condition 3) demonstrate that it is possible to comply with the maximum storage volume of the goods.

The proposed changes list d325 shows an example of displaying a table showing the contents of the proposed changes to the order conditions information o1.

Furthermore, the list of proposed changes (d325) may display all the calculated proposed changes to the order conditions, the index number for each change, the details of the condition changes, and the change in the maximum capacity utilization rate.

Pressing (clicking) the edit button d33 for the proposed changes may allow administrators or users to directly edit the proposed changes, or pressing the start negotiation button d34 may lead to step S15 in Figure 11.

Next, we will return to Figure 11 and describe the details of steps S13 to S19. The negotiation unit f2 saves the progress of the processing in steps S13 to S19. Based on the saved data, the screen generation unit f3 generates display data for a confirmation screen of the automatic negotiation execution status, which can then be output from the input/output interface 13 and displayed on a display device or the like.

Figure 17 shows an example of the display of the confirmation screen d4 for checking the execution status of automated negotiations. The confirmation screen d4 includes an area d41 for displaying the negotiation result information o2 shown in Figure 9, and a negotiation end button d42.

Area d41 may display the order of negotiation execution (negotiation order #181), the index number of the proposed change in conditions being negotiated (proposed change in conditions #182), the change in the maximum capacity utilization due to the change in conditions (storage 183, receiving operation 184), the maximum capacity utilization under the ordering conditions at the start of the negotiation process in step S15 (storage 185, receiving operation 186), and the negotiation status 187. Alternatively, pressing the "end negotiation" button d42 may terminate the negotiation process midway and proceed to step S20.

Next, returning to Figure 11, we will describe the details of steps S20 to S22. The negotiation unit f2 modifies the order conditions agreed upon through the above negotiation process (S20). Then, the negotiation unit f2 determines whether the updated order condition change proposal information o1 meets the capacity limit (S21). If the capacity limit is not met, the negotiation unit f2 proceeds to step S22, where it calculates the required amount of external resources to compensate for the capacity excess and can arrange for them. Furthermore, the negotiation unit f2 saves the details of the arranged external resources in the external resource arrangement proposal information o3, and the screen generation unit f3 generates display data for the external resource quantity confirmation and arrangement screen based on the saved content, which can then be output from the input/output interface 13 and displayed on a display device or the like.

Figure 18 shows an example of the display of the external resource quantity confirmation and arrangement screen d5. The confirmation and arrangement screen d5 includes an area d51 that displays a list of the external resources needed to compensate for the capacity excess after negotiations, and a negotiation start button d52.

Area d51 can display elements of the external resource procurement plan information o3 shown in Figure 10. This may include the capacity type 191 exceeding the site-specific capacity information i2 (such as storage and CO2 emissions), the resource type 192 to compensate for the excess capacity, the required amount of external resources 193, the required period 194, the proposed procurement plan 195, and the total cost increase 196 resulting from the procurement.

In the example shown in Figure 18, even after automated negotiations, storage capacity will be exceeded, requiring an external warehouse of 1,000 tsubo (approximately 3,300 square meters) from December 1, 2022 to January 10, 2023. Two proposed arrangements are presented: Warehouse P, which would increase the total cost by $1.0 million, and Warehouse Q, which would increase the total cost by $1.1 million.

When the negotiation start button d52 is pressed, starting with the offer proposal with the smallest total cost increase of 196, the system may automatically begin negotiations on the offers 195 for the same ability type 191, starting with the offer with the smallest total cost increase of 196. The negotiation status may also be displayed (not shown).

In the above examples, we have shown a method for generating new inventory supply plans and ordering conditions by generating all possible combinations or by increasing or decreasing some quantities in the provisional solutions, in order to search for the Pareto optimal solution. However, the present invention is not limited to this method, and the Pareto optimal solution may also be formulated using mathematical optimization techniques, such as mixed integer programming.
<Conclusion>

As described above, the inventory supply planning system 1 of this embodiment generates proposed order condition changes for each product and quantitatively evaluates the reduction in capacity utilization at the logistics center (or base) for each proposed change. This allows for efficient negotiation with suppliers, prioritizing the proposals with the largest capacity utilization reductions. As a result, it is possible to determine order conditions that comply with the base's capacity and are acceptable to the supplier.

Furthermore, the inventory supply planning system 1 of the above embodiment can be configured as follows:

(1) An inventory supply planning method for a computer (inventory supply planning system 1) having an arithmetic unit (processor 11) and memory (14) accessible by the arithmetic unit (11), wherein the computer (1) includes an initial inventory quantity (product-specific/location-specific initial inventory information i6) indicating the inventory quantity for each item at the location, capacity information (location-specific capacity information i2) which sets a capacity upper limit index (upper limit) for each item relating to the upper limit of the capacity of the location, unit load information (product information i1) which sets a unit load for each item at the location, and the item An inventory supply planning method characterized by comprising: a first step (S10) of acquiring pre-set ordering conditions for each item (product-specific ordering condition information i3); a second step (S11) in which the computer (1) calculates an initial inventory supply plan for each item that satisfies the upper limit of the ordering conditions (i1); and a third step (S12) in which the computer (1) calculates proposed changes to the ordering conditions for each item so that the capacity is reduced, based on an ordering condition change index, and calculates the inventory supply plan based on the ordering condition change index as a modified inventory supply plan (04).

The above configuration allows for quantitative evaluation of the reduction in capacity utilization at logistics centers and other locations, thereby ensuring compliance with the capacity of the locations and determining order conditions that are acceptable to suppliers.

(2) An inventory supply planning method as described in (1) above, characterized in that, in the third step (S12), the ratio of the capacity used by the item to the capacity upper limit index in the initial inventory supply plan is calculated as the first capacity occupancy rate, the capacity used by the item to the capacity upper limit index in the modified inventory supply plan (o4) is calculated as the second capacity occupancy rate, the value obtained by subtracting the second capacity occupancy rate from the first capacity occupancy rate is calculated as the reduction amount (175, 176), and this reduction amount is set as the value of the order condition determination index.

The above configuration makes it possible to quantitatively evaluate the reduction in capacity utilization due to proposed changes in ordering conditions for each product at logistics centers and other locations.

(3) An inventory supply planning method as described in (2) above, characterized in that, in the third step (S12), proposed changes to the ordering conditions are searched for for each item so as to satisfy the capacity information (i2).

With the above configuration, it becomes possible to determine the Pareto-optimal proposed changes to ordering conditions by exploring options for each product while adhering to the capabilities of logistics centers and other bases.

(4) An inventory supply planning method as described in (2) above, further comprising a fourth step (S15) in which the computer (1) selects the proposed changes to the ordering conditions for each item in descending order of the reduction amounts (175, 176), transmits the selected proposed changes to the ordering conditions to the supplier of the item, and negotiates whether or not to accept the proposed changes to the ordering conditions.

With the above configuration, by quantitatively evaluating the reduction in capacity utilization due to proposed changes in ordering conditions for each product at logistics centers and other locations, it becomes possible to efficiently negotiate with suppliers, starting with the changes that result in the largest reduction in capacity utilization relative to the location's capacity.

(5) An inventory supply planning method as described in (4) above, characterized in that, in the fourth step (S15), if the proposed changes to the ordering conditions are not accepted, negotiations are repeated for the next proposed changes to the ordering conditions in order of the largest reduction amounts (175, 176).

The above configuration allows for repeated negotiation of proposed changes to order terms until they are accepted, thereby reducing the effort required when proposing changes to order terms for each product.

(6) An inventory supply planning method as described in (1) above, further comprising a fifth step (S22) in which the computer (1) calculates an external resource arrangement plan (o3) utilizing external resources (5) of the site if the proposed changes to the ordering conditions do not satisfy the capacity information (i2).

With the above configuration, if the capabilities of a single location are insufficient, it becomes possible to devise a revised ordering condition that utilizes external resources, thereby enabling the effective use of resources across multiple locations.

(7) An inventory supply planning method as described in (6) above, characterized in that, in the fifth step (S22), an instruction is transmitted to the provider of the external resource (5) to arrange the external resource based on the proposed external resource arrangement (o3).

With the above configuration, if the capabilities of a single location are insufficient, it becomes possible to arrange for the use of external resources, thereby reducing the effort required when utilizing resources from multiple locations.

(8) An inventory supply planning method as described in (1) above, characterized in that, in the second step (S11), the transport volume for each product, daily, and route that satisfies the capacity information (i2) is determined, the inbound/outbound volume and inventory volume (stock(t, w, i)) are calculated from the transport volume, and an inventory supply plan (o4) consisting of the transport volume, inbound/outbound volume and inventory volume (stock(t, w, i)) is calculated.

The above configuration makes it possible to quantitatively evaluate the reduction in capacity utilization due to proposed changes in ordering conditions for each product at logistics centers and other locations.

(9) An inventory supply planning method as described in (1) above, characterized in that, in the second step (S11), the capacity information (i2) includes at least one of the following as the capacity upper limit indicator of the base: inventory storage capacity, CO2 emission capacity, receiving capacity, and shipping capacity, and calculates an inventory supply plan for each item that satisfies the capacity upper limit indicator in addition to the ordering conditions (i1) and the upper limit of the stockout rate (123).

The above configuration makes it possible to formulate an inventory supply plan o4 that satisfies inventory storage capacity, CO2 emission capacity, at least one capacity upper limit indicator for receiving capacity and shipping capacity, a stockout rate upper limit 114, and ordering conditions.

(10) An inventory supply planning method as described in (8) above, characterized in that, in the second step (S11), the cost of implementing the inventory supply plan (o4) is calculated as the total cost (totCost), the CO2 emissions when the inventory supply plan is implemented are calculated, the inventory value (aveInventory) when the inventory supply plan is implemented is calculated, the cash flow when the inventory supply plan is implemented is calculated, and the inventory supply plan is output that minimizes the total cost (totCost), CO2 emissions, and inventory value (aveInventory), and maximizes the cash flow.

With the above configuration, it becomes possible to output an inventory supply plan o4 that optimizes total cost, CO2 emissions, inventory value, and cash flow as key performance indicators (KPIs).

(16) An inventory supply planning method as described in (1) above, characterized in that, in the first step, the unit load information (i1) has a predetermined upper limit (123) for the stockout rate at the base for each item; in the second step, an inventory supply plan for each item that satisfies the ordering conditions and the upper limit (123) for the stockout rate is calculated as an initial inventory supply plan (initial inventory information i6 by item and base); and in the third step, ordering condition change range information (i6) has a predetermined range of acceptable changes to the ordering conditions for each item, and a proposed change to the ordering conditions is calculated for each item based on the ordering condition change index so that the capacity is reduced within the acceptable range.

With the above configuration, it is possible to calculate order conditions that meet the ordering requirements and stockout rate limits for each location, without exceeding the capacity of each location, and that are acceptable to the supplier.

Furthermore, the present invention is not limited to the embodiments described above, and various modifications are included. For example, the embodiments described above are detailed for the purpose of clearly illustrating the present invention and are not necessarily limited to those that include all the configurations described. Also, it is possible to replace parts of the configuration of one embodiment with those of another embodiment, and it is also possible to add configurations from other embodiments to the configuration of one embodiment. Moreover, for parts of the configuration of each embodiment, the addition, deletion, or substitution of other configurations can be applied individually or in combination.

Furthermore, each of the above-described configurations, functions, processing units, and processing means may be implemented in hardware, either partially or entirely, for example, by designing them as integrated circuits. Alternatively, each of the above-described configurations and functions may be implemented in software by a processor interpreting and executing programs that implement each function. Information such as programs, tables, and files that implement each function can be stored in memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD.

Furthermore, the control and information lines shown are those deemed necessary for explanatory purposes and do not necessarily represent all control and information lines in the actual product. In practice, it can be assumed that almost all components are interconnected.

1. Inventory Supply Planning System 2. Storage Device 11. Processor 14. Memory f1. Order Condition Change Proposal Planning Unit f2. Negotiation Unit f3. Screen Generation Unit i1. Product Information i2. Location-Specific Capacity Information i3. Product-Specific Order Condition Information i4. Product-Specific Order Condition Change Acceptable Range Information i5. Daily, Product-Specific, and Demand Forecast Information i6. Product-Specific and Location-Specific Initial Inventory Information o1. Order Condition Change Proposal Information o2. Negotiation Result Information o3. External Resource Arrangement Proposal Information o4. Inventory Supply Plan o41. Daily, Product-Specific, and Route-Specific Transportation Information o42. Daily, Vehicle-Specific, and Route-Specific Transportation Quantity Information o43. Daily, Vehicle-Specific, and Location-Specific Inbound/Outbound and Inventory Quantity Information

Claims (13)

A computer having a computing device and a memory accessible by the computing device, which plans the inventory of each item to be stored at a location, is used as an inventory supply planning method.
The first step involves the computer receiving a target location to be processed and acquiring: initial inventory quantities by product and location for managing the inventory quantity of each item at each of the multiple locations; capacity information by location for managing a capacity limit index, which is the upper limit of the capacity of each of the multiple locations; unit load information set for each of the multiple locations for managing the load per unit of each item; order condition information by product for managing the order conditions for the order quantity of each item at the target location; demand forecast information for managing the demand forecast for each item at the target location; and change tolerance information for managing the range of change tolerance for the order conditions for each item .
The second step is for the computer to use the initial inventory quantity by product and location, the capacity information by location, the unit load information, the ordering conditions information by product, and the demand forecast information to calculate an initial inventory supply plan for each item that is below the upper limit of the stockout rate and below the upper limit of the capacity index of the target location .
A third step in which the computer calculates, based on the site-specific capacity information and the unit load information, for each item a first capacity occupancy rate, which is the ratio of the capacity used by the item to the capacity upper limit index in the initial inventory supply plan, and a second capacity occupancy rate, which is the ratio of the capacity used by the item to the capacity upper limit index in the inventory supply plan generated by changing the ordering conditions within the permissible range of changes to the ordering conditions, calculates the reduction amount by subtracting the second capacity occupancy rate from the first capacity occupancy rate, and calculates a proposed change to the ordering conditions for each item such that the reduction amount is Pareto optimal.
The computer performs a fourth step of selecting from the proposed condition changes a condition change proposal that satisfies the predetermined condition regarding the reduction amount,
A fifth step in which the computer modifies the product-specific ordering condition information using the selected proposed changes for each item, and calculates a revised inventory supply plan using the initial inventory quantity for each product and location, the capacity information for each location, the unit load information, the modified product-specific ordering condition information, and the demand forecast information .
A method for planning inventory supply, characterized by including the following: The inventory supply planning method according to claim 1,
In the fourth step described above,
An inventory supply planning method characterized by selecting the proposed change in conditions that maximizes the amount of reduction . The inventory supply planning method according to claim 2,
An inventory supply planning method further comprising a sixth step in which the computer selects the proposed changes in terms and conditions for each item in order of the largest reduction amount, transmits the selected changes in terms and conditions to the supplier of the item, and negotiates whether or not to accept the changes in terms and conditions. The inventory supply planning method according to claim 3,
In the sixth step described above,
If the aforementioned proposed changes to the conditions are not accepted, the method of inventory supply planning is characterized by repeatedly negotiating for the next proposed changes to the conditions in order of the amount of reduction. The inventory supply planning method according to claim 1,
An inventory supply planning method further comprising a seventh step in which the computer calculates an external resource arrangement plan that utilizes resources outside the target location if the capacity of the target location to which the modified inventory supply plan is applied is not less than or equal to the capacity upper limit indicator of the target location. The inventory supply planning method according to claim 5,
In the seventh step described above,
An inventory supply planning method characterized by transmitting an instruction to the provider of the external resources to arrange the external resources based on the proposed external resource arrangement. The inventory supply planning method according to claim 1,
In the fifth step described above,
An inventory supply planning method characterized by determining the transport volume by item, day by day and by route such that the capacity of the target base to which the revised inventory supply plan is applied is less than or equal to the capacity upper limit index of the target base, calculating the inbound/outbound volume and inventory volume from the transport volume, and calculating the revised inventory supply plan including the transport volume, inbound/outbound volume and inventory volume. The inventory supply planning method according to claim 1,
The inventory supply planning method is characterized in that the aforementioned capacity is at least one of inventory storage capacity, CO2 emission capacity, and inventory receiving capacity and inventory shipping capacity. The inventory supply planning method according to claim 7,
In the fifth step described above,
An inventory supply planning method characterized by calculating the total cost when the inventory supply plan is implemented, calculating the CO2 emissions when the inventory supply plan is implemented, calculating the inventory value when the inventory supply plan is implemented, calculating the cash flow, and outputting the inventory supply plan in which any of the total cost, CO2 emissions, or inventory value is minimized, or the cash flow is maximized. An inventory supply planning system including a computer having a computing device and a memory accessible by the computing device,
The aforementioned computer is
The computing device receives a target location to be processed and acquires: initial inventory quantities by product and location for managing the inventory quantity of each item at each of the multiple locations; capacity information by location for managing the capacity limit index, which is the upper limit of the capacity of each of the multiple locations; unit load information set for each of the multiple locations for managing the load per unit of each item; order condition information by product for managing the order conditions for the order quantity of each item at the target location; demand forecast information for managing the demand forecast for each item at the target location; and change tolerance information for managing the range of change tolerance for the order conditions for each item.
The calculation device uses the initial inventory quantity for each product and location, the capacity information for each location, the unit load information, the ordering conditions information for each product, and the demand forecast information to calculate an initial inventory supply plan for each item that is below the upper limit of the stockout rate and below the upper limit of the capacity index of the target location.
The calculation device calculates, based on the site-specific capacity information and the unit load information, for each item, a first capacity occupancy rate which is the ratio of the capacity used by the item to the capacity upper limit index in the initial inventory supply plan, and a second capacity occupancy rate which is the ratio of the capacity used by the item to the capacity upper limit index in the inventory supply plan generated by changing the ordering conditions within the permissible range for changes to the ordering conditions, and calculates the reduction amount by subtracting the second capacity occupancy rate from the first capacity occupancy rate, and for each item, calculates a proposed change to the ordering conditions within the permissible range for changes to the ordering conditions such that the reduction amount is Pareto optimal.
The calculation unit selects from the proposed condition changes that the reduction amount satisfies the predetermined conditions,
An inventory supply planning system characterized in that the calculation device modifies the product-specific ordering condition information using the selected condition change proposal for each item, and calculates a modified inventory supply plan using the initial inventory quantity for each product and location, the capacity information for each location, the unit load information, the modified product-specific ordering condition information, and the demand forecast information. The inventory supply planning system according to claim 10,
An inventory supply planning system characterized in that, when the calculation device selects the proposed change in conditions, it selects the proposed change in conditions that maximizes the amount of reduction. The inventory supply planning system according to claim 11,
An inventory supply planning system characterized in that the computing device selects the proposed condition changes for each item in order of the largest reduction amount, transmits the selected condition changes to the supplier of the item, and negotiates whether or not to accept the condition changes. The inventory supply planning system according to claim 12,
An inventory supply planning system characterized in that, if the calculation unit does not accept the proposed change in conditions, it repeatedly negotiates for the next proposed change in conditions in order of the amount of reduction.