Method, device, equipment, medium and program product for formulating goods delivery plan

Abstract

The present application belongs to the field of data processing technology, and specifically relates to a method, device, equipment, medium and program product for formulating a goods delivery plan. The present application aims to solve the problems of delayed delivery of goods, high warehouse storage costs and transportation costs that may exist in the prior art. The method includes: obtaining at least one goods order, according to the identification of each goods, obtaining the priority of each goods in each warehouse, and the reserve quantity of each goods in each warehouse, inputting the latest delivery date of each goods, the preset date range, the priority of each goods in each warehouse, and the demand for each goods into the objective function, and obtaining the delivery plan corresponding to each goods order according to the constraints of the objective function. In this technical solution, the multi-objective optimization algorithm in linear optimization is used to reduce the time cost, warehouse storage cost and transportation cost caused by the formulation of incorrect plans, and ensure the timeliness of goods delivery.

Description

Technical Field

[0001] The embodiments of the present application belong to the field of data processing technology, and specifically relate to a method, device, equipment, medium and program product for formulating a goods delivery plan. Background Art

[0002] For manufacturers who produce goods, they usually need to produce goods according to the orders issued by the sales shops and formulate corresponding delivery plans for the goods. The accurate formulation of the goods delivery plan can improve business conversion, thereby achieving and improving the visibility of the manufacturer. Therefore, how to formulate the goods delivery plan is the key.

[0003] At present, the formulation of product delivery plans mainly involves manufacturers sending orders from sales shops to the warehouses closest to the sales shops after receiving the orders. After each warehouse receives the orders from the manufacturers, it determines the planned delivery date based on the latest delivery date of all orders received by the warehouse, thereby formulating a delivery plan for each order, so that each warehouse can subsequently send the goods in the order to the corresponding sales shops according to the delivery plan.

[0004] However, the above scheme takes fewer factors into consideration in the process of formulating the goods delivery plan, and cannot guarantee a reasonable delivery plan. There may be problems such as untimely delivery of goods, high warehouse storage costs and high transportation costs. Summary of the invention

[0005] In order to solve the above-mentioned problems in the prior art, that is, to solve the problems of untimely delivery of goods, high warehouse storage costs and high transportation costs that may exist in the prior art, the embodiments of the present application provide a method, device, equipment, medium and program product for formulating a goods shipment plan.

[0006] In a first aspect, an embodiment of the present application provides a method for formulating a goods delivery plan, comprising:

[0007] Obtain at least one product order, each product order including a product identifier, a latest delivery date of the product, and a demand quantity of the product;

[0008] According to the identification of each product, obtain the priority of each product in each warehouse and the reserve quantity of each product in each warehouse, wherein the priority is determined according to the production date of the product in each warehouse;

[0009] The latest delivery date of each product, the preset date range, the priority of each product in each warehouse, and the demand for each product are input into the objective function, and the delivery plan corresponding to each product order is obtained according to the constraints of the objective function; wherein the delivery plan includes the target delivery date and the target warehouse, and the constraints are determined according to the reserve quantity of each product in each warehouse, the maximum daily delivery quantity of each warehouse, the preset allocation ratio, the actual production volume of each product in each warehouse, and the preset maximum allocation quantity.

[0010] In the preferred technical solution of the above method for formulating a goods delivery plan, the constraints include:

[0011] Items in each order cannot be shipped from multiple warehouses and / or shipped according to multiple shipping dates;

[0012] The total shipment amount of all goods of each warehouse on any day within the shippable date range cannot exceed the maximum daily shipment amount of each warehouse, and the shippable date range is determined based on the preset date range and the latest shipment date of each product;

[0013] The shipment quantity of each product in each warehouse cannot exceed the sum of the reserve quantity of the product in the warehouse and the transfer quantity of the product;

[0014] The total transfer quantity of each product cannot exceed the sum of the reserve quantities of the product in all warehouses;

[0015] The total amount of each item that can be allocated to each warehouse on any day within the said delivery date range cannot exceed the said preset maximum allocation amount. The said total amount that can be allocated is determined based on the said preset allocation ratio and the actual production volume of the said item in other warehouses except the said warehouse.

[0016] In the preferred technical solution of the method for formulating the above-mentioned product delivery plan, the latest delivery date of each product, the preset date range, the priority of each product in each warehouse, and the demand for each product are input into the objective function, and the delivery plan corresponding to each product order is obtained according to the constraint conditions of the objective function, including:

[0017] The latest shipping date of each product, the preset date range, the priority of each product in each warehouse, and the demand for each product are input into the objective function, and the shipping date and warehouse of each product order that minimizes the value of the objective function are determined as the target shipping date and target warehouse for each product order based on the constraints of the objective function.

[0018] In the preferred technical solution of the above method for formulating a product delivery plan, the step of obtaining at least one product order includes:

[0019] Obtaining an initial product order, the initial product order including a product identifier, a latest delivery date for the product, and a demand quantity for the product;

[0020] When the product is an air conditioner set, the initial product order is split into two product orders according to the mapping relationship among the identifier of the air conditioner set, the identifier of the air conditioner indoor unit and the identifier of the air conditioner outdoor unit.

[0021] In the preferred technical solution of the method for formulating the above-mentioned goods delivery plan, when the target delivery date in any delivery plan is postponed, the target warehouse in the delivery plan is none.

[0022] In the preferred technical solution of the method for formulating the above-mentioned goods delivery plan, the step of obtaining the priority of each goods in each warehouse according to the identification of each goods includes:

[0023] According to the identification of each product, obtain the production date of the product in each warehouse;

[0024] Sort each warehouse in ascending order according to the production date of the goods in each warehouse, and obtain the priority of each goods in each warehouse based on the sorting result.

[0025] In a second aspect, an embodiment of the present application provides a device for formulating a goods delivery plan, comprising:

[0026] An acquisition module, used to acquire at least one product order, each product order including a product identifier, a latest delivery date of the product, and a demand quantity of the product;

[0027] The acquisition module is further used to acquire the priority of each commodity in each warehouse and the reserve quantity of each commodity in each warehouse according to the identification of each commodity, wherein the priority is determined according to the production date of the commodity in each warehouse;

[0028] The processing module is used to input the latest delivery date of each product, the preset date range, the priority of each product in each warehouse, and the demand for each product into the objective function, and obtain the delivery plan corresponding to each product order according to the constraint conditions of the objective function; wherein the delivery plan includes the target delivery date and the target warehouse, and the constraint conditions are determined according to the reserve quantity of each product in each warehouse, the maximum delivery quantity of each warehouse per day, the preset allocation ratio, the actual production quantity of each product in each warehouse, and the preset maximum allocation quantity.

[0029] In the preferred technical solution of the above-mentioned device for formulating a goods delivery plan, the constraint conditions include:

[0030] Items in each order cannot be shipped from multiple warehouses and / or shipped according to multiple shipping dates;

[0031] The total shipment amount of all goods of each warehouse on any day within the shippable date range cannot exceed the maximum daily shipment amount of each warehouse, and the shippable date range is determined based on the preset date range and the latest shipment date of each product;

[0032] The shipment quantity of each product in each warehouse cannot exceed the sum of the reserve quantity of the product in the warehouse and the transfer quantity of the product;

[0033] The total transfer quantity of each product cannot exceed the sum of the reserve quantities of the product in all warehouses;

[0034] The total amount of each item that can be allocated to each warehouse on any day within the said delivery date range cannot exceed the said preset maximum allocation amount. The said total amount that can be allocated is determined based on the said preset allocation ratio and the actual production volume of the said item in other warehouses except the said warehouse.

[0035] In the preferred technical solution of the above-mentioned device for formulating a goods delivery plan, the processing module is specifically used to:

[0036] The latest shipping date of each product, the preset date range, the priority of each product in each warehouse, and the demand for each product are input into the objective function, and the shipping date and warehouse of each product order that minimizes the value of the objective function are determined as the target shipping date and target warehouse for each product order based on the constraints of the objective function.

[0037] In the preferred technical solution of the above-mentioned device for formulating a goods delivery plan, the acquisition module is specifically used to:

[0038] Obtaining an initial product order, the initial product order including a product identifier, a latest delivery date for the product, and a demand quantity for the product;

[0039] When the product is an air conditioner set, the initial product order is split into two product orders according to the mapping relationship among the identifier of the air conditioner set, the identifier of the air conditioner indoor unit and the identifier of the air conditioner outdoor unit.

[0040] In the preferred technical solution of the device for formulating the above-mentioned goods delivery plan, when the target delivery date in any delivery plan is postponed, the target warehouse in the delivery plan is not available.

[0041] In the preferred technical solution of the above-mentioned device for formulating a goods delivery plan, the acquisition module is specifically used to:

[0042] According to the identification of each product, obtain the production date of the product in each warehouse;

[0043] Sort each warehouse in ascending order according to the production date of the goods in each warehouse, and obtain the priority of each goods in each warehouse based on the sorting result.

[0044] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor, a memory, and computer program instructions stored in the memory and executable on the processor, wherein the processor is used to implement the first aspect and the methods provided by various possible designs when executing the computer program instructions.

[0045] In a fourth aspect, an embodiment of the present application may provide a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect and the methods provided by various possible designs.

[0046] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, is used to implement the first aspect and the methods provided by various possible designs.

[0047] It is understandable to those skilled in the art that the method, device, equipment, medium and program product for formulating a goods delivery plan provided in the embodiments of the present application obtain at least one goods order, obtain the priority of each goods in each warehouse and the reserve quantity of each goods in each warehouse according to the identification of each goods, input the latest delivery date of each goods, the preset date range, the priority of each goods in each warehouse, and the demand for each goods into the objective function, and obtain the delivery plan corresponding to each goods order according to the constraints of the objective function. This scheme utilizes the multi-objective optimization algorithm in linear optimization, takes into account various factors that may affect the formulation of the delivery plan, and formulates a reasonable delivery plan under the constraints of limited conditions and on the premise of meeting the requirements of the business, thereby reducing the time cost, warehouse storage cost and transportation cost caused by the formulation of an erroneous plan, ensuring the timeliness of goods delivery, and maximizing economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The following describes the preferred implementation of the method, device, equipment, medium and program product for formulating a goods delivery plan of the present application with reference to the accompanying drawings. The accompanying drawings are:

[0049] Figure 1 A schematic diagram of an application scenario of the method for formulating a goods delivery plan provided in an embodiment of the present application;

[0050] Figure 2A flowchart of a method for formulating a goods delivery plan according to an embodiment of the present application;

[0051] Figure 3 A schematic diagram of the structure of a device for formulating a goods delivery plan provided in an embodiment of the present application;

[0052] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] First, those skilled in the art should understand that these implementations are only used to explain the technical principles of the present application and are not intended to limit the scope of protection of the present application. Those skilled in the art can make adjustments to them as needed to adapt to specific application scenarios.

[0054] Secondly, it should be noted that in the description of the embodiments of the present application, terms such as "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and does not indicate or imply that the device or component must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present application.

[0055] In addition, it should be noted that in the description of the embodiments of the present application, unless otherwise clearly specified and limited, the terms "connected" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0056] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0057] Before introducing the embodiments of the present application, the application background of the embodiments of the present application is first explained:

[0058] For larger manufacturers, they usually have multiple warehouses to produce and store goods together. Generally, multiple warehouses are usually set up in multiple locations and are dispersed, so that they can save certain logistics costs when delivering goods to surrounding sales shops. In order to improve business conversion and realize and increase the visibility of manufacturers, corresponding delivery plans can be formulated according to the orders issued by sales shops, and the goods can be shipped according to the delivery date in the delivery plan, so as to ensure that the goods can be delivered to the sales shops on time and improve the satisfaction of the sales shops.

[0059] At present, the formulation of product delivery plans is mainly that manufacturers send the orders to the warehouse closest to the sales store based on the address of the sales store that places the order. After receiving the order, the warehouse sorts all the orders from small to large according to the latest delivery date in the orders. The planned delivery dates of the orders at the front are smaller, and the planned delivery dates of the orders at the back are larger. In this way, a corresponding delivery plan is formulated for each order, so that each warehouse can subsequently send the goods in the order to the corresponding sales store according to the delivery plan.

[0060] However, the above scheme takes fewer factors into consideration in the process of formulating the goods delivery plan, and cannot guarantee a reasonable delivery plan. There may be problems such as untimely delivery of goods, high warehouse storage costs and high transportation costs.

[0061] In view of the above problems, the invention of this application is as follows: the prior art only considers the impact of factors such as the location of the sales store, the location of the warehouse, and the latest delivery date on the delivery plan, and does not consider the various factors that can affect the formulation of the delivery plan, as well as the impact of various factors on the delivery plan, resulting in an inability to guarantee a reasonable delivery plan. Based on this, the inventor found that when formulating a delivery plan, if the factors such as the location of the store, the location of the warehouse, and the latest delivery date are combined with the consideration of the reserve quantity of each product in each warehouse, the production date of each product in each warehouse, etc., and all factors are processed through the objective function and the corresponding constraints, and the unique delivery date and delivery warehouse are obtained from multiple aspects such as transportation cost, warehouse storage cost, and product loss cost, the problem of the inability to guarantee a reasonable delivery plan in the prior art can be solved, thereby improving the timeliness of product delivery and reducing warehouse storage costs and transportation costs.

[0062] For example, the method for formulating a goods delivery plan provided in the embodiment of the present application can be applied to Figure 1 In a schematic diagram of an application scenario shown in FIG. Figure 1 A schematic diagram of an application scenario of the method for formulating a goods delivery plan provided in the embodiment of the present application is used to solve the above technical problems. Figure 1As shown, the application scenario may include: a server and a sales store terminal device.

[0063] In this embodiment, the sales store can send a product order to the server. Accordingly, the server can receive the product order sent by the sales store, and then process the product order, and obtain the delivery plan corresponding to the order by running the program of the method for formulating a product delivery plan. Furthermore, the electronic device can also send the delivery plan to the corresponding target warehouse in the delivery plan, so that the target warehouse can subsequently deliver the goods according to the target delivery date in the delivery plan.

[0064] In practical applications, since the terminal device is also a processing device with data processing capabilities, the above Figure 1 The server in the application scenario shown can also be implemented by a terminal device. In the embodiment of the present application, the server and the terminal device for data processing can be collectively referred to as an electronic device.

[0065] The technical solution of the present application is described in detail below through specific embodiments.

[0066] It should be noted that the following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0067] Figure 2 The flowchart of the method for formulating a goods delivery plan provided in the embodiment of the present application is shown in FIG. Figure 2 As shown, the method for formulating the goods delivery plan may include the following steps:

[0068] S21. Obtain at least one product order.

[0069] In a possible implementation, the electronic device may obtain a product order sent by a sales shop terminal device, may receive multiple product orders sent by a sales shop terminal device, and may also receive multiple product orders sent by multiple sales shop terminal devices.

[0070] In another possible implementation, the electronic device may obtain an initial product order sent by a terminal device of a sales store, the initial product order including the product identification, the latest delivery date of the product, and the demand for the product. When the product in the initial product order is an air conditioner set, the initial product order is split into two product orders according to the mapping relationship between the identification of the air conditioner set, the identification of the air conditioner indoor unit, and the identification of the air conditioner outdoor unit; when the product in the initial product order is a product other than an air conditioner set, the initial product is confirmed as a product order.

[0071] Exemplarily, the mapping relationship among the identification of the air conditioner set, the identification of the air conditioner indoor unit and the identification of the air conditioner outdoor unit can be obtained from a relationship mapping table pre-entered by a staff member. The relationship mapping table can be shown in Table 1.

[0072] Table 1

[0073] Air conditioning unit logo Air conditioner indoor unit logo Air conditioner outdoor unit logo Air conditioning unit logo 1 Air conditioner indoor unit logo 1 Air conditioner outdoor unit logo 1 Air conditioning unit logo 2 Air conditioner indoor unit logo 2 Air conditioner outdoor unit logo 2 Air conditioning unit logo 3 Air conditioner indoor unit logo 3 Air conditioner outdoor unit logo 3

[0074] Taking the mapping relationship shown in Table 1 as an example, if the identifier of the air-conditioning set in the initial product order is air-conditioning set identifier 2, the electronic device can split the initial product order into two product orders, and the identifiers of the products in the two product orders are air-conditioning indoor unit identifier 2 and air-conditioning outdoor unit identifier 2 respectively.

[0075] Among them, the sales store terminal device can be a mobile phone, tablet computer, or computer, etc.

[0076] Each product order includes the product identification, the latest delivery date of the product, and the demand for the product. For example, the product may be a washing machine, a refrigerator, an air conditioner and other household appliances, or may be food, daily necessities and other types of products. In some embodiments, the product order may also include an order type and an order number.

[0077] S22. According to the identification of each commodity, obtain the priority of each commodity in each warehouse and the reserve quantity of each commodity in each warehouse.

[0078] Among them, the priority is determined according to the production date of the goods in each warehouse. In some embodiments, the electronic device can obtain the production date of the goods in each warehouse according to the identification of each product, sort each warehouse according to the production date of the goods in each warehouse from small to large, and obtain the priority of each product in each warehouse according to the sorting result. For example, taking the goods in the goods order as refrigerators as an example, the electronic device obtains the production date of the refrigerator of this model in each warehouse according to the identification of the refrigerator (such as the refrigerator model). If there are multiple refrigerators of this model in any warehouse, the average of the production dates of multiple refrigerators of this model is used as the production date of the refrigerator of this model in the warehouse. The production dates of the refrigerators of this model in each warehouse are sorted in order from small to large, the priority of the warehouse ranked first is determined to be 1, and the priority of the warehouse ranked second is determined to be 2, and all warehouses are traversed to obtain the priorities of all warehouses.

[0079] Optionally, the electronic device may also obtain a production plan for each warehouse, where the production plan includes the actual production volume of the goods in each warehouse and the identification of the warehouse.

[0080] In the above two steps S21 and S22, in some embodiments, the electronic device can parse the goods order to obtain the identification of the goods, the latest delivery date of the goods, and the demand for the goods through a preset parsing algorithm. Exemplarily, the electronic device can determine the identification of the goods, the latest delivery date of the goods, and the demand for the goods by reading the field at the preset position in the goods order. The electronic device can also parse the production plan and inventory data of each warehouse to obtain the reserve quantity of each product in each warehouse, etc. How the electronic device reads the field at the preset position in the target order can refer to any existing implementation method, which will not be repeated here.

[0081] Furthermore, after the electronic device obtains the identification of the above-mentioned goods, the latest delivery date of the goods, the demand for the goods, and the reserve quantity of each product in each warehouse, it can also uniformly encode the above-mentioned data and standardize the data format.

[0082] S23. The latest delivery date of each product, the preset date range, the priority of each product in each warehouse, and the demand for each product are input into the objective function, and the delivery plan corresponding to each product order is obtained according to the constraints of the objective function.

[0083] Among them, the delivery plan includes the target delivery date and the target warehouse.

[0084] In a specific implementation method, the latest delivery date of each product, the preset date range, the priority of each product in each warehouse, and the demand for each product are input into the objective function, and the delivery date and warehouse of each product order that minimizes the value of the objective function are determined as the target delivery date and target warehouse for each product order based on the constraints of the objective function.

[0085] Among them, the objective function can be expressed by the formula: L = loss 1 +loss 2 +loss 3 +loss 4 The minimum value of the objective function can be achieved by solving the formula: min L. Where L is the cost of implementing the delivery plan, loss 1 is the delayed delivery cost, loss 2 Delayed order cost, loss 3 is the transportation cost, loss 4 It is the cost of goods loss. 1 , loss 2 , loss 3 , loss 4 It can be realized by the following formulas respectively.

[0086] 1) Since the delayed delivery cost is proportional to the time difference between the latest delivery date and the target delivery date, the loss 1 This can be achieved through the following formula:

[0087]

[0088] Among them, k 0 , k 1 is the preset weight coefficient, is the time difference between the latest delivery date and the target delivery date of the product order o, which is a positive integer. max(D) is the maximum value of the delivery date range, and min(D) is the minimum value of the delivery date range. The delivery date range is determined based on the preset date range and the latest delivery date of each product. For example, the preset date range is the time range for the user to make a delivery plan. For example, if a manufacturer needs to obtain the delivery plan for each product order in May, the preset date range is from May 1 to 31. At this time, if the latest delivery date of the product order is November 20, the delivery date range is from May 1 to 31; if the latest delivery date of the product order is May 20, the delivery date range is from May 1 to 20.

[0089] 2), loss 2 The formula loss can be used 2 =k 2 ×∑ o delay o，p Implementation, where k 2 is the preset weight coefficient, delay o，p Whether the product order o is postponed is a binary type. The above postponement means that the product order o is not shipped within the available shipping date range.

[0090] 3), loss 3 The formula loss can be used 3 =k 3 *∑ o v o，w，d，p Implementation, where k 3 is the preset weight coefficient, v o，w，d，p Whether item p in item order o on date d is shipped from warehouse w, which is a binary type.

[0091] 4), loss 4 This can be achieved through the following formula:

[0092]

[0093] Among them, k 4 is the preset weight coefficient, is the priority of item p of item order o in warehouse w, vo，w，d Whether the goods in order o for date d are shipped in warehouse w, n o，p is the demand for item p of item order o.

[0094] The constraints are determined based on the reserve quantity of each item in each warehouse, the maximum daily shipment volume of each warehouse, the preset allocation ratio, the actual production volume of each item in each warehouse, and the preset maximum allocation volume.

[0095] Among them, when the target delivery date in any delivery plan is postponed, the target warehouse in the delivery plan is none.

[0096] Exemplarily, after obtaining a product order, the electronic device may generate an initial delivery schedule based on the data in the product order. The initial delivery schedule may be as shown in Table 2.

[0097] Table 2

[0098]

[0099] Furthermore, after obtaining the target shipping date and target warehouse corresponding to each order, the target shipping date and target warehouse corresponding to each order can be added to Table 2 to generate Table 3.

[0100] Table 3

[0101]

[0102] As shown in Table 3, for order O 1 For example, the corresponding delivery plan is May 9, 2021 from w 1 Warehouse for shipment.

[0103] The method for formulating a goods delivery plan provided in the embodiment of the present application obtains at least one goods order, obtains the priority of each goods in each warehouse and the reserve quantity of each goods in each warehouse according to the identification of each goods, inputs the latest delivery date of each goods, the preset date range, the priority of each goods in each warehouse, and the demand for each goods into the objective function, and obtains the delivery plan corresponding to each goods order according to the constraint conditions of the objective function. This scheme utilizes the multi-objective optimization algorithm in linear optimization, takes into account various factors that may affect the formulation of the delivery plan, and formulates a reasonable delivery plan under the constraints of limited conditions and on the premise of meeting the requirements of the business, thereby reducing the time cost, warehouse storage cost and transportation cost caused by the formulation of an erroneous plan, ensuring the timeliness of goods delivery, and maximizing economic benefits.

[0104] Optionally, in some embodiments, the constraints include:

[0105] 1) The goods in each order cannot be shipped from multiple warehouses and / or cannot be shipped according to multiple shipping dates. The formula can be used: ∑ d ∑ w v o，w，d =1 indicates.

[0106] 2) The total shipment volume of all goods in each warehouse on any day within the shipping date range cannot exceed the maximum daily shipment volume of each warehouse, which can be calculated by the formula: It indicates that, is the maximum daily shipment volume of warehouse w.

[0107] 3) The shipment quantity of each product in each warehouse cannot exceed the sum of the storage quantity of the product in the warehouse and the total transfer quantity of the product. This can be calculated by the formula: ∑ p n o，p ≤r w，p，d +t d，p，w Indicates that r w，p，d is the reserve quantity of product p in warehouse w, t d，p，w The quantity of item p transferred to warehouse w on date d.

[0108] 4) The total transfer quantity of each product cannot exceed the sum of the reserve quantities of the product in all warehouses, which can be calculated by the formula: d，p，w ≤r w，p，d express.

[0109] 5) The total transfer quantity of each item in each warehouse on any day within the delivery date range cannot exceed the preset maximum transfer quantity, which can be calculated by the formula: ∑ p ∑ w v d，p，w ≤M means, where v d，p，w is whether the product p is shipped in warehouse w on date d, and M is the preset maximum transfer quantity, which is a positive integer. The total transfer quantity is determined based on the preset transfer ratio and the actual production volume of the products in warehouses other than the warehouse. If the preset transfer ratio is T n , the total amount that can be transferred is the actual production volume of the goods in warehouses other than the warehouse multiplied by T n , the actual production volume of goods in warehouses other than the warehouse is multiplied by (1-T n ) is the quantity available for transfer the next day.

[0110] In addition, constraints can also include: the goods of the same product order need to be shipped from the same warehouse, which can be achieved through the formula: Indicates that v o，p，w，d Whether item p in item order o on date d is shipped from warehouse w.

[0111] Optionally, in some embodiments, a transfer plan for goods in each warehouse may be formulated according to the delivery plan for each order, wherein the transfer plan may be as shown in Table 4.

[0112] Table 4

[0113]

[0114] As shown in Table 4, for product p 0 For example, the allocation plan is d 0 Date will be goods p 0 Transfer to w 0 storehouse indivual.

[0115] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0116] Figure 3 This is a schematic diagram of the structure of the device for formulating a goods delivery plan provided in an embodiment of the present application. Figure 3 As shown, the device for formulating the goods delivery plan includes:

[0117] The acquisition module 31 is used to acquire at least one product order, each product order includes a product identifier, a latest delivery date of the product, and a demand quantity of the product;

[0118] The acquisition module 31 is further used to acquire the priority of each commodity in each warehouse and the reserve quantity of each commodity in each warehouse according to the identification of each commodity, and the priority is determined according to the production date of the commodity in each warehouse;

[0119] The processing module 32 is used to input the latest delivery date of each product, the preset date range, the priority of each product in each warehouse, and the demand for each product into the objective function, and obtain the delivery plan corresponding to each product order according to the constraints of the objective function; wherein the delivery plan includes the target delivery date and the target warehouse, and the constraints are determined according to the reserve quantity of each product in each warehouse, the maximum daily delivery quantity of each warehouse, the preset allocation ratio, the actual production quantity of each product in each warehouse, and the preset maximum allocation quantity.

[0120] In a possible design of an embodiment of the present application, the constraints include:

[0121] Items in each order cannot be shipped from multiple warehouses and / or shipped according to multiple shipping dates;

[0122] The total shipment volume of all products from each warehouse on any day within the shippable date range cannot exceed the maximum daily shipment volume of each warehouse. The shippable date range is determined based on the preset date range and the latest shipping date of each product.

[0123] The shipment quantity of each product in each warehouse cannot exceed the sum of the warehouse's reserve quantity and the total transfer quantity of the product;

[0124] The total transfer quantity of each product cannot exceed the sum of the reserve quantities of the product in all warehouses;

[0125] The total amount of each item that can be transferred to each warehouse on any day within the shipping date range cannot exceed the preset maximum transfer amount. The total amount of items that can be transferred is determined based on the preset transfer ratio and the actual production volume of items in warehouses other than the warehouse.

[0126] In a possible design of an embodiment of the present application, the processing module 32 is specifically configured to:

[0127] The latest delivery date of each product, the preset date range, the priority of each product in each warehouse, and the demand for each product are input into the objective function. According to the constraints of the objective function, the delivery date and warehouse of each product order that minimizes the value of the objective function are determined as the target delivery date and target warehouse for each product order.

[0128] In a possible design of the embodiment of the present application, the acquisition module 31 is specifically used to:

[0129] Obtaining an initial product order, the initial product order includes a product identifier, a latest delivery date of the product, and a demand quantity of the product;

[0130] When the goods are air-conditioning sets, the initial goods order is split into two goods orders according to the mapping relationship among the identification of the air-conditioning set, the identification of the air-conditioning indoor unit and the identification of the air-conditioning outdoor unit.

[0131] In a possible design of an embodiment of the present application, when the target delivery date in any delivery plan is postponed, the target warehouse in the delivery plan is none.

[0132] In a possible design of the embodiment of the present application, the acquisition module 31 is specifically used to:

[0133] According to the identification of each product, obtain the production date of the products in each warehouse;

[0134] Sort each warehouse in ascending order according to the production date of the goods in each warehouse, and obtain the priority of each goods in each warehouse based on the sorting result.

[0135] The device for formulating a goods delivery plan provided in the embodiment of the present application can be used to execute the method for formulating a goods delivery plan in any of the above embodiments. Its implementation principle and technical effects are similar and will not be repeated here.

[0136] It should be noted that it should be understood that the division of the various modules of the above device is only a division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated. And these modules can all be implemented in the form of software calling through processing elements; they can also be all implemented in the form of hardware; some modules can also be implemented in the form of software calling through processing elements, and some modules can be implemented in the form of hardware. In addition, all or part of these modules can be integrated together, or they can be implemented independently. The processing element described here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each module above can be completed by an integrated logic circuit of hardware in the processor element or instructions in the form of software.

[0137] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 4 As shown, the electronic device may include: a processor 41, a memory 42, and computer program instructions stored in the memory 42 and executable on the processor 41. When the processor 41 executes the computer program instructions, the method for formulating a goods shipment plan provided in any of the aforementioned embodiments is implemented.

[0138] Optionally, the electronic device may further include an interface for interacting with other devices.

[0139] Optionally, the above-mentioned components of the electronic device may be connected via a system bus.

[0140] The memory 42 may be a separate storage unit or a storage unit integrated in the processor. The number of processors is one or more.

[0141] It should be understood that the processor 41 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the present application can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor.

[0142] The system bus may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The system bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus. The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage.

[0143] All or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a readable memory. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned memory (storage medium) includes: read-only memory (ROM), RAM, flash memory, hard disk, solid state drive, magnetic tape, floppy disk, optical disc and any combination thereof.

[0144] The electronic device provided in the embodiment of the present application can be used to execute the method for formulating a goods delivery plan provided in any of the above-mentioned method embodiments. Its implementation principle and technical effects are similar and will not be repeated here.

[0145] An embodiment of the present application provides a computer-readable storage medium, in which computer instructions are stored. When the computer instructions are executed on a computer, the computer executes the method for formulating the above-mentioned goods delivery plan.

[0146] The computer-readable storage medium mentioned above can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory, electrically erasable programmable read-only memory, erasable programmable read-only memory, programmable read-only memory, read-only memory, magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0147] Optionally, a readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0148] An embodiment of the present application also provides a computer program product, which includes a computer program, and the computer program is stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium, and when the at least one processor executes the computer program, the method for formulating the above-mentioned goods shipping plan can be implemented.

[0149] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for formulating a goods delivery plan, characterized in that: include: Obtain at least one product order, each product order including a product identifier, a latest delivery date of the product, and a demand quantity of the product; According to the identification of each commodity, obtain the priority of each commodity in each warehouse and the reserve quantity of each commodity in each warehouse, wherein the priority is determined according to the commodity in each warehouse; The latest delivery date of each product, the preset date range, the priority of each product in each warehouse, and the demand for each product are input into the objective function, and the delivery plan corresponding to each product order is obtained according to the constraint conditions of the objective function; wherein the delivery plan includes the target delivery date and the target warehouse, and the constraint conditions are determined according to the reserve quantity of each product in each warehouse, the maximum delivery quantity of each warehouse per day, the preset allocation ratio, the actual production quantity of each product in each warehouse, and the preset maximum allocation quantity; The objective function is represented by the formula: L=loss1+loss2+loss3+loss4, where loss1 is the delayed delivery cost, loss2 is the delayed order cost, loss3 is the transportation cost, and loss4 is the product loss cost; loss1, loss2, loss3, and loss4 are respectively implemented by the following formulas; Among them, k0, k1 are preset weight coefficients, is the time difference between the latest delivery date of the product order o and the target delivery date, max(D) is the maximum value of the available delivery date range, min(D) is the minimum value of the available delivery date range, and the available delivery date range is determined based on the preset date range and the latest delivery date of each product; loss2=k2×∑ o delay o，p Among them, k2 is the preset weight coefficient, delay o，p Whether the product order o is delayed is a binary type. The above delay means that the product order o is not shipped within the available shipping date range; loss3=k3*∑ o v o，w,d，p Among them, k3 is the preset weight coefficient, v o，w,d，p Whether the item p in the item order o on date d is shipped in warehouse w, which is a binary type; Among them, k4 is the preset weight coefficient, is the priority of item p of item order o in warehouse w, v o,w,d Whether the goods in order o for date d are shipped in warehouse w, n o,p is the demand for item p of item order o.

2. The method according to claim 1, characterized in that The constraints include: Items in each order cannot be shipped from multiple warehouses and / or shipped according to multiple shipping dates; The total shipment amount of all goods of each warehouse on any day within the shippable date range cannot exceed the maximum daily shipment amount of each warehouse, and the shippable date range is determined based on the preset date range and the latest shipment date of each product; The shipment quantity of each product in each warehouse cannot exceed the sum of the reserve quantity of the product in the warehouse and the transfer quantity of the product; The total transfer quantity of each product cannot exceed the sum of the reserve quantities of the product in all warehouses; The total amount of each item that can be allocated to each warehouse on any day within the said delivery date range cannot exceed the said preset maximum allocation amount. The said total amount that can be allocated is determined based on the said preset allocation ratio and the actual production volume of the said item in other warehouses except the said warehouse.

3. The method according to claim 1 or 2, characterized in that: The latest delivery date of each product, the preset date range, the priority of each product in each warehouse, and the demand for each product are input into the objective function, and the delivery plan corresponding to each product order is obtained according to the constraint conditions of the objective function, including: The latest shipping date of each product, the preset date range, the priority of each product in each warehouse, and the demand for each product are input into the objective function, and the shipping date and warehouse of each product order that minimizes the value of the objective function are determined as the target shipping date and target warehouse for each product order based on the constraints of the objective function.

4. The method according to claim 1, characterized in that: The obtaining of at least one product order comprises: Obtaining an initial product order, the initial product order including a product identifier, a latest delivery date for the product, and a demand quantity for the product; When the product is an air conditioner set, the initial product order is split into two product orders according to the mapping relationship among the identifier of the air conditioner set, the identifier of the air conditioner indoor unit and the identifier of the air conditioner outdoor unit.

5. The method according to claim 1, characterized in that When the target delivery date in any delivery plan is postponed, the target warehouse in the delivery plan is none.

6. The method according to claim 1, characterized in that The step of obtaining the priority of each product in each warehouse according to the identification of each product includes: According to the identification of each product, obtain the production date of the product in each warehouse; Sort each warehouse in ascending order according to the production date of the goods in each warehouse, and obtain the priority of each goods in each warehouse based on the sorting result.

7. A device for formulating a goods delivery plan, characterized in that: include: An acquisition module, used to acquire at least one product order, each product order including a product identifier, a latest delivery date of the product, and a demand quantity of the product; The acquisition module is further used to acquire the priority of each commodity in each warehouse and the reserve quantity of each commodity in each warehouse according to the identification of each commodity, wherein the priority is determined according to the production date of the commodity in each warehouse; A processing module is used to input the latest delivery date of each product, a preset date range, the priority of each product in each warehouse, and the demand for each product into an objective function, and obtain a delivery plan corresponding to each product order according to the constraint conditions of the objective function; wherein the delivery plan includes a target delivery date and a target warehouse, and the constraint conditions are determined according to the reserve quantity of each product in each warehouse, the maximum delivery quantity of each warehouse per day, the preset allocation ratio, the actual production quantity of each product in each warehouse, and the preset maximum allocation quantity; The objective function is represented by the formula: L=loss1+loss2+loss3+loss4, where loss1 is the delayed delivery cost, loss2 is the delayed order cost, loss3 is the transportation cost, and loss4 is the product loss cost; loss1, loss2, loss3, and loss4 are respectively implemented by the following formulas; Among them, k0, k1 are preset weight coefficients, is the time difference between the latest delivery date of the product order o and the target delivery date, max(D) is the maximum value of the available delivery date range, min(D) is the minimum value of the available delivery date range, and the available delivery date range is determined based on the preset date range and the latest delivery date of each product; loss2=k2×∑ o delay o，p Among them, k2 is the preset weight coefficient, delay o，p Whether the product order o is delayed is a binary type. The above delay means that the product order o is not shipped within the available shipping date range; loss3=k3*∑ o v o，w,d，p Among them, k3 is the preset weight coefficient, v o，w,d，p Whether the item p in the item order o on date d is shipped in warehouse w, which is a binary type; Among them, k4 is the preset weight coefficient, is the priority of item p of item order o in warehouse w, v o，w,d Whether the goods in order o for date d are shipped in warehouse w, n o，p is the demand for item p of item order o.

8. An electronic device, comprising: A processor, a memory, and computer program instructions stored in the memory and executable on the processor, wherein the processor is used to implement the method for formulating a goods shipment plan as described in any one of claims 1 to 6 when executing the computer program instructions.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method for formulating a goods shipment plan as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that: When the computer program is executed by a processor, it is used to implement the method for formulating a goods shipment plan as described in any one of claims 1 to 6.

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