WO2019001099A1 - 信息推送方法和装置 - Google Patents

信息推送方法和装置 Download PDF

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Publication number
WO2019001099A1
WO2019001099A1 PCT/CN2018/083373 CN2018083373W WO2019001099A1 WO 2019001099 A1 WO2019001099 A1 WO 2019001099A1 CN 2018083373 W CN2018083373 W CN 2018083373W WO 2019001099 A1 WO2019001099 A1 WO 2019001099A1
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Prior art keywords
product
warehouse
products
determining
mathematical model
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PCT/CN2018/083373
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English (en)
French (fr)
Inventor
景雷
李聚信
冯卓
尹航
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Beijing Jingdong Century Trading Co Ltd
Beijing Jingdong Shangke Information Technology Co Ltd
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Beijing Jingdong Century Trading Co Ltd
Beijing Jingdong Shangke Information Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computing arrangements based on specific mathematical models

Definitions

  • the present application relates to the field of computer technologies, and in particular, to the field of Internet technologies, and in particular, to an information push method and apparatus.
  • the existing method usually searches for inventory information at each judgment and further screens by determining the advantages and disadvantages of different schemes. If there are multiple schemes with the same degree of superiority and inferiority, it will enter a more detailed judgment until the final identification is unique.
  • the warehouse therefore, has problems such as low flexibility.
  • the purpose of the embodiments of the present application is to provide an improved information pushing method and apparatus to solve the technical problems mentioned in the above background art.
  • an embodiment of the present application provides an information pushing method, which includes: extracting inventory information of a product to be processed and a product to be processed, wherein the inventory information includes an inventory of each warehouse in which the product is stored and Pre-inventory ratio of the product in each warehouse; parsing the processed order and inventory information, determining at least one target warehouse in the warehouse where the product is stored, for the outbound product; based on each of the at least one target warehouse in the product
  • the inventory in the target warehouse, the preset inventory ratio, and the demand quantity of the products recorded in the pending order determine the quantity of the products to be shipped out from the respective target warehouses; and the push includes the pending warehouses corresponding to the determined target warehouses.
  • the amount of information includes: extracting inventory information of a product to be processed and a product to be processed, wherein the inventory information includes an inventory of each warehouse in which the product is stored and Pre-inventory ratio of the product in each warehouse; parsing the processed order and inventory information, determining at least one target warehouse in the warehouse where the
  • the inventory information further includes preset outbound request information; and parsing the processed order and inventory information to determine at least one target warehouse in the warehouse in which the product is stored for the outbound product, including: Determining the priority of each warehouse in which the product is stored based on the outbound request information, and determining the weight corresponding to each priority; establishing a mathematical model based on the determined weight and the priority of each warehouse, and determining the optimal mathematical model The solution determines each warehouse indicated by the optimal solution as a target warehouse for the outbound product.
  • establishing a mathematical model based on the determined weights and priorities of the respective warehouses, and determining an optimal solution for the mathematical model includes determining a quantity of products of the product to be processed and a solution to the mathematical model Quantity; determine the solution method based on the number of products of the product involved in the order to be processed and/or the number of solutions of the mathematical model, and determine the optimal solution of the mathematical model using the determined solution.
  • the solution is determined based on the number of products of the product to be processed and/or the number of solutions of the mathematical model, and the determined solution is used to determine the optimal solution of the mathematical model, including: in response to determining The number of products is less than the first preset number, and the optimal solution of the mathematical model is determined based on the greedy algorithm.
  • the solution is determined based on the number of products of the product to be processed and/or the number of solutions of the mathematical model, and the determined solution is used to determine the optimal solution of the mathematical model, including: in response to determining The number of products is not less than the first preset number and the number of solutions is less than the second preset number, and the optimal solution of the mathematical model is determined based on the constraint planning method.
  • the solution is determined based on the number of products of the product to be processed and/or the number of solutions of the mathematical model, and the determined solution is used to determine the optimal solution of the mathematical model, including: in response to determining The number of products is not less than the first preset number and the number of solutions is not less than the second preset number, and the optimal solution of the mathematical model is determined by combining the greedy algorithm and the constraint planning method.
  • an embodiment of the present application provides an information pushing apparatus, where the apparatus includes: an extracting unit configured to extract inventory information of a product to be processed and a product to be processed, wherein the inventory information includes a product stored therein The inventory of each warehouse and the preset inventory ratio of the products in each warehouse; the parsing unit configured to parse the order and inventory information to be processed, and determine at least one target warehouse in the warehouse in which the product is stored for the outbound product a determining unit configured to determine, based on the inventory of the product in each of the target warehouses in the at least one target warehouse, the preset inventory ratio, and the quantity of the products recorded in the pending order, determining the products to be delivered from the respective target warehouses The number of outbounds; the pushing unit is configured to push information including the determined number of inbound and outbound corresponding to each target warehouse.
  • the inventory information further includes preset outbound request information; and the parsing unit includes: a first determining module configured to determine a priority of each warehouse in which the product is stored based on the outbound request information, and determine a weight corresponding to each priority; a second determining module configured to establish a mathematical model based on the determined weight and priority of each warehouse, and determine an optimal solution of the mathematical model, and each of the warehouses indicated by the optimal solution Determined to be the target warehouse for the outbound product.
  • the second determining module includes: a first determining submodule configured to determine a quantity of products of the product to be processed and a number of solutions of the mathematical model; and a second determining submodule configured to be based on The number of products of the product to be processed and/or the number of solutions of the mathematical model, determine the solution method, and determine the optimal solution of the mathematical model by using the determined solution.
  • the second determining sub-module is further configured to determine an optimal solution of the mathematical model based on the greedy algorithm in response to determining that the number of products is less than the first predetermined number.
  • the second determining submodule is further configured to: determine, according to the constraint planning method, an optimal solution of the mathematical model in response to determining that the number of products is not less than the first predetermined number and the number of solutions is less than the second predetermined number .
  • the second determining submodule is further configured to: determine, in response to the greedy algorithm and the constraint planning method, the mathematical model in response to determining that the number of products is not less than the first predetermined number and the number of solutions is not less than the second predetermined number The optimal solution.
  • an embodiment of the present application provides a server, including: one or more processors; and a storage device, configured to store one or more programs, when one or more programs are executed by one or more processors, One or more processors are enabled to implement a method as in any of the embodiments of the information push method.
  • an embodiment of the present application provides a computer readable storage medium, where a computer program is stored, wherein the program is executed by a processor to implement a method such as any one of the information pushing methods.
  • the information pushing method and device determine the target warehouse by parsing the extracted pending order and inventory information, and then determining each based on the inventory of each warehouse, the preset inventory ratio, and the demand quantity of the product.
  • the number of outbound warehouses for each product increases the flexibility of order processing.
  • FIG. 1 is an exemplary system architecture diagram to which the present application can be applied;
  • FIG. 2 is a flow chart of one embodiment of an information push method according to the present application.
  • FIG. 3 is a schematic diagram of an application scenario of an information pushing method according to the present application.
  • FIG. 5 is a schematic structural diagram of an embodiment of an information pushing apparatus according to the present application.
  • FIG. 6 is a block diagram showing the structure of a computer system suitable for implementing the server of the embodiment of the present application.
  • FIG. 1 illustrates an exemplary system architecture 100 in which an information push method or information push device of the present application may be applied.
  • system architecture 100 can include data storage server 101, inventory server 102, network 103, and order processing server 104.
  • the network 103 is used as a medium for providing a communication link between the data storage server 101, the inventory server 102, and the order processing server 104.
  • Network 102 can include a variety of connection types, such as wired, wireless communication links, fiber optic cables, and the like.
  • the data storage server 101 can store various information such as information to be processed, inventory information, information of products stored in each warehouse (for example, production date, shelf life, etc.), and user-set outbound requirements.
  • the inventory server 102 can communicate with the terminal devices (not shown) deployed in the respective warehouses, and send information of products of the warehouses to be out of the warehouse (which may include the product code, the number of products to be shipped out, etc.) to each The terminal device deployed in the warehouse.
  • the warehouse management personnel can carry out product selection by the information displayed by the above terminal equipment, or send an instruction to the picking robot to perform product sorting and the like.
  • the order processing server 104 can interact with the data storage server 101 and the inventory server 102 via the network 103, respectively, to receive or send messages and the like.
  • the order processing server 104 can acquire the to-be-processed order, inventory information, and the like stored by the data storage server 101, and can also analyze and process the acquired information, and process the result (for example, products and quantities of multiple warehouses to be shipped out, etc.) ) Pushed to the inventory server 102.
  • the order processing server 104 may also have the functions of the data storage server 101 and the inventory server 102.
  • the system architecture 100 may not include the data storage server 101 and the inventory server 102.
  • the information pushing method provided by the embodiment of the present application is generally performed by the server 104. Accordingly, the information pushing device is generally disposed in the server 104.
  • the information pushing method includes the following steps:
  • Step 201 Extract inventory information of products to be processed and products involved in the pending order.
  • the electronic device (such as the order processing server 104 shown in FIG. 1) on which the information push method operates can extract inventory information of products to be processed and products involved in the order to be processed.
  • the above-mentioned pending order may be an order of a warehouse in which the product is not determined to be shipped out.
  • the inventory information of the products involved in the above-mentioned pending order may include the inventory of each warehouse in which the above products are stored (here, the inventory amount) and the preset inventory ratio of each warehouse of the above products.
  • a product is in stock at the first warehouse, the second warehouse, and the third warehouse, and the preset inventory ratio in the first warehouse, the second warehouse, and the third warehouse is 8:1:1.
  • the inventory information of the product to be processed and the product to be processed may be pre-stored in the electronic device.
  • the electronic device may directly extract the to-be-processed order and the inventory information from the local.
  • the above-mentioned pending order and the above inventory information may also be stored in another server (for example, the data storage server 101 shown in FIG. 1).
  • the electronic device may be from the server through a wired connection or a wireless connection.
  • the above-mentioned pending order and the above inventory information are extracted.
  • the URL is generally represented by a Uniform Resource Locator (URL).
  • wireless connection manner may include but is not limited to 3G/4G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods that are now known or developed in the future. .
  • Step 202 Analyze the processing order and the inventory information, and determine at least one target warehouse in the warehouse in which the product is stored for exporting the product.
  • the electronic device may analyze the to-be-processed order and the inventory information by using various analysis methods to determine at least one target warehouse in the warehouse in which the product is stored for exporting the product.
  • the electronic device may determine whether there is a warehouse in the warehouse in which the product related to the order to be processed is stored, which can satisfy the product demand of the to-be-processed order, and if present, the warehouse that meets the demand and is to be processed
  • the delivery address recorded in the order is determined as the target warehouse from the nearest warehouse; if not, the two warehouses in the warehouse in which the products related to the above-mentioned pending orders are stored are combined to determine whether the above-mentioned pending orders are satisfied.
  • a set of warehouses for product demand if present, select one of the required warehouses, and determine the selected warehouse as the target warehouse. If not, the third of the warehouses of the products involved in the above-mentioned pending orders will be stored. The warehouses are combined, and so on, until at least one target warehouse for the above products is identified.
  • Step 203 Determine, based on the inventory of the product in each target warehouse in the at least one target warehouse, the preset inventory ratio, and the required quantity of the product recorded in the to-be-processed order, determine that the product is out of the target warehouse.
  • the number of libraries The number of libraries.
  • the electronic device may determine the target from each target based on the inventory of the product in each target warehouse in the at least one target warehouse, the preset inventory ratio, and the demand quantity of the product recorded by the to-be-processed order.
  • the warehouse will release the number of products to be shipped out of the above products.
  • the electronic device may first determine a current inventory ratio of the products in each of the target warehouses in the at least one target warehouse. Then, the electronic device can know the current inventory ratio and the demand quantity of the above-mentioned products recorded by the to-be-processed order, and solve the problem that the inventory ratio after each target warehouse is out of the same or the same as the preset inventory ratio.
  • Each target warehouse stores the number of products to be shipped out of the above products.
  • a product is in stock in the first warehouse, the second warehouse, and the third warehouse, and the preset inventory ratio in the first warehouse, the second warehouse, and the third warehouse is 2:2:1,
  • the inventory of the product in the first warehouse, the second warehouse and the third warehouse is 30, 10, 10 respectively, that is, the current inventory ratio is 3:1:1, and if the demand quantity of the product is 30, the above
  • the number of pending shipments corresponding to the first warehouse is 22, the number of pending shipments corresponding to the second warehouse is 2, and the number of pending shipments corresponding to the third warehouse is 6.
  • Step 204 Push information including the determined number of to-be-outs corresponding to each target warehouse.
  • the electronic device may push information including the determined number of items to be shipped corresponding to each target warehouse.
  • the electronic device can push the information to a server for managing inventory (e.g., inventory server 102 shown in Figure 1).
  • a server for managing inventory e.g., inventory server 102 shown in Figure 1.
  • the above information may also include the names of the respective target warehouses, the product information of the above products, and the above-mentioned pending orders.
  • FIG. 3 is a schematic diagram of an application scenario of the information pushing method according to the embodiment.
  • the order processing server 301 may first extract the pending order 303 and the inventory information 304 of the product involved in the pending order from the data storage server 302, and the inventory information 304 includes the above products in each The preset inventory ratio of the warehouse.
  • the order processing server 301 can then parse the at least one target repository 305 with respect to the processing order 303 and the inventory information 304. after that.
  • the order processing server 301 can determine, based on the inventory of the products in the respective target warehouses, the preset inventory ratio, and the required quantity of the above products recorded in the to-be-processed order, the number 306 of the products to be shipped out from the respective target warehouses. Finally, the order processing server 301 can push the information 307 containing the determined number of warehousings 306 corresponding to the respective target warehouses to the inventory server 308.
  • the method provided by the foregoing embodiment of the present application by using the information pushing method and device provided by the embodiment of the present application, by analyzing the extracted pending order and inventory information to determine the target warehouse, and then based on the inventory of each warehouse, The inventory ratio and the demand quantity of the product are determined, the number of the warehouses to be delivered corresponding to each target warehouse is determined, and finally the information including the determined quantity of the warehouse to be delivered is pushed, so that not only the warehouse for the products involved in the delivery order but also the warehouse for the products involved in the delivery order can be determined.
  • the flexibility of order processing is enhanced by the flexibility to adjust the number of outbound warehouses for each of the products involved in the outbound order.
  • the flow 400 of the information pushing method includes the following steps:
  • Step 401 Extract inventory information of products to be processed and products involved in the pending order.
  • the information push method operates with the electronic device thereon (e.g., the order processing server 104 shown in Fig. 1) to extract the inventory information of the product to be processed and the product to be processed.
  • the above-mentioned pending order may be an order of a warehouse in which the product is not determined to be shipped out.
  • the inventory information of the products involved in the above-mentioned pending order may include the inventory of each warehouse in which the above products are stored and the preset inventory ratio of each warehouse of the above products.
  • Step 402 Determine, according to the outbound request information, the priorities of the respective warehouses in which the products are stored, and determine the weights corresponding to the respective priorities.
  • the inventory information may further include preset outbound request information.
  • the above-mentioned delivery requirements may include, but are not limited to, products that are close to the shelf life of the product, and products that are stored in a certain warehouse are preferentially out of the library.
  • the electronic device may first determine the priority of each warehouse in which the product is stored based on the outbound request information, and determine the weight corresponding to each priority.
  • the priority of the warehouse can be divided into three levels, which are respectively the first priority from high to low (for example, the above-mentioned products stored in a warehouse are close to the shelf life, then the priority of the warehouse can be determined to be the first Priority), second priority (for example, the actual inventory ratio of the above product in a warehouse is greater than the preset inventory ratio, then the priority of the warehouse can be determined as the second priority) and the third priority (for example, The priority of the remaining warehouses other than the first priority and the second priority described above is determined as the third priority).
  • the weight corresponding to each priority may be any value (for example, 0.2, 0.5, or 0.8, etc.) preset by a technician.
  • Step 403 based on the determined weights and priorities of the respective warehouses, establish a mathematical model, and determine an optimal solution of the mathematical model, and determine each warehouse indicated by the optimal solution as a target warehouse for the outbound storage of the above products.
  • the electronic device may establish a mathematical model based on the determined weights and priorities of the respective warehouses.
  • the above electronic device can establish a mathematical model by the following steps:
  • S represents any product S involved in the above-mentioned pending order
  • W represents any warehouse in which the products involved in the above-mentioned pending order are stored
  • J SW may be 1 or 0 to indicate whether the product S is in the warehouse W.
  • I W may be 1 or 0 to indicate whether the warehouse W has shipped out at least one of the products involved in the above-mentioned pending order, that is, whether the warehouse W is used.
  • I W is 1, it means that the warehouse W is used; when I W is 0, it means that the warehouse W is not used.
  • the above constraint I W ⁇ J SW indicates that if the product S is out of the warehouse W, the warehouse W is used.
  • the following mathematical model can be established based on the priority of the warehouse and the weight of each priority of each product in which the above-mentioned pending orders are stored:
  • the above P 1 , P 2 , and P 3 respectively represent a set of warehouses storing the first priority of any of the products S involved in the order to be processed, and storing any product S involved in the to-be-processed order; a set of warehouses of a second priority, storing a set of warehouses of a third priority of any of the products S involved in the order to be processed; the above W 1 , W 2 , and W 3 respectively represent weights corresponding to the first priority The weight corresponding to the second priority and the weight corresponding to the third priority; the above W 0 is used to indicate the weight of the total number of used warehouses, and the foregoing W 0 may be preset by the technician based on a large amount of data statistics and calculations. Any value greater than W 1 , W 2 , and W 3 , respectively.
  • the above electronic device can also establish the constraints of the above mathematical model:
  • the electronic device may determine the optimal solution of the mathematical model by using various solution methods (such as a heuristic algorithm such as a greedy algorithm, and an exact solution method such as constraint planning and integer programming), and indicate the optimal solution.
  • Each warehouse is determined to be the target warehouse for the above products.
  • the above optimal solution is the value of each J SW and I W when the minimum value of the mathematical model is above.
  • the above electronic device can also solve the minimum value of the sum of I W , that is, the minimum used warehouse total.
  • the electronic device may first determine the number of products (refer to the number of types of products) of the product involved in the order to be processed and the number of solutions of the mathematical model; and then The solution mode is determined based on the number of products of the product involved in the order to be processed and/or the number of solutions of the above mathematical model, and the optimal solution of the mathematical model is determined by the determined solution manner.
  • the electronic device in response to determining that the number of products is less than a first predetermined number (eg, five), may determine an optimal solution of the mathematical model based on a greedy algorithm.
  • the greedy algorithm also known as the greedy algorithm
  • the electronic device may determine an optimal solution of the mathematical model based on a greedy algorithm.
  • the greedy algorithm also known as the greedy algorithm
  • the greedy algorithm means that when solving the problem, always make the best choice at the present time. That is to say, instead of considering the overall optimality, what he is doing is a local optimal solution in a certain sense.
  • the above electrons can directly determine the above-mentioned local optimal solution obtained by using the greedy algorithm as the optimal solution of the above mathematical model.
  • the greedy algorithm is used to solve the above mathematical model for the case where the number of products is smaller than the first preset number, that is, when the number of products is small, the above partial optimal solution obtained by using the greedy algorithm is usually The optimal solution of the above mathematical model or the solution closer to the optimal solution is therefore more accurate.
  • the electronic device in response to determining that the number of products is not less than the first preset number and the number of the solutions is less than a second preset number (eg, 100,000), the electronic device may be based on The constraint planning method determines the optimal solution of the above mathematical model.
  • Constraint Programming is a computational technique for studying constrained combinatorial optimization problems. It can use the efficient constrained propagation and search mechanism to quickly obtain feasible solutions to the problem and determine the optimal solution.
  • the above constraint propagation is also called consistency check or preprocessing technology, which is used to answer whether the problem has a feasible solution; the above search mechanism usually uses a tree search algorithm to search for the next variable to be assigned and experiment by depth-first search.
  • constraints differ from the imperative programming language elements in that they do not explicitly state one of the steps to be performed, but rather some properties that define their solution. Therefore, the constraint programming method can be used to solve the above mathematical model and obtain an optimal solution.
  • the electronic device in response to determining that the number of products is not less than the first preset number and the number of the solutions is not less than the second preset quantity, may combine the greedy algorithm and The above constraint planning method determines the optimal solution of the above mathematical model.
  • the minimum used warehouse total may be determined by the constraint planning method, and then the greedy algorithm is used to determine the optimal solution in the case of satisfying the minimum used warehouse total, that is, the values of the respective J SW and I W .
  • Step 404 determining, based on the inventory of the products in the target warehouses in the at least one target warehouse, the preset inventory ratio, and the required quantity of the products recorded in the to-be-processed order, determining that the products are discharged from the respective target warehouses.
  • the number of libraries The number of libraries.
  • the electronic device may determine the target from each target based on the inventory of the product in each target warehouse in the at least one target warehouse, the preset inventory ratio, and the demand quantity of the product recorded by the to-be-processed order.
  • the warehouse will release the number of products to be shipped out of the above products.
  • the electronic device may first determine a current inventory ratio of the products in each of the target warehouses in the at least one target warehouse. Then, the electronic device can know the current inventory ratio and the demand quantity of the above-mentioned products recorded by the to-be-processed order, and solve the problem that the inventory ratio after each target warehouse is out of the same or the same as the preset inventory ratio.
  • Each target warehouse stores the number of products to be shipped out of the above products.
  • Step 405 Push information including the determined number of to-be-outs corresponding to each target warehouse.
  • the electronic device may push information including the determined number of items to be shipped corresponding to each target warehouse.
  • the electronic device can push the information to a server for managing inventory (e.g., inventory server 102 shown in Figure 1).
  • a server for managing inventory e.g., inventory server 102 shown in Figure 1.
  • the above information may also include the names of the respective target warehouses, the product information of the above products, and the above-mentioned pending orders.
  • the flow 400 of the information push method in the present embodiment highlights the steps of determining a target warehouse by establishing a mathematical model and using different algorithms to find an optimal solution, as compared to the embodiment corresponding to FIG. Therefore, the solution described in this embodiment can use different algorithms to determine the target warehouse of the optimal solution indication for the complexity of the order, which can not only reduce the production cost of the order, but also improve the processing efficiency of the order.
  • the present application provides an embodiment of an information pushing apparatus, and the apparatus embodiment corresponds to the method embodiment shown in FIG. Used in a variety of electronic devices.
  • the information pushing apparatus 500 of this embodiment includes: an extracting unit 501 configured to extract inventory information of a to-be-processed order and a product related to the to-be-processed order, wherein the inventory information includes The inventory of each warehouse of the above products and the preset inventory ratio of the above products in each warehouse; the parsing unit 502 is configured to parse the above-mentioned pending orders and the above inventory information, and determine in the warehouse in which the products are stored, Determining at least one target warehouse of the above products; determining unit 503, configured to store the inventory in each target warehouse in the at least one target warehouse based on the product, the preset inventory ratio, and the above-mentioned product recorded in the to-be-processed order The quantity of the demand determines the number of the products to be shipped out from the respective target warehouses; the pushing unit 504 is configured to push the information including the determined number of the outbound warehouses corresponding to the respective target warehouses.
  • the extracting unit 501 can extract the inventory information of the product to be processed and the product involved in the order to be processed.
  • the above-mentioned pending order may be an order of a warehouse in which the product is not determined to be shipped out.
  • the inventory information of the products involved in the above-mentioned pending order may include the inventory of each warehouse in which the above products are stored and the preset inventory ratio of each warehouse of the above products.
  • the parsing unit 502 may parse the to-be-processed order and the inventory information by using various analysis methods to determine at least one target warehouse in the warehouse in which the product is stored for exporting the product.
  • the determining unit 503 may determine, based on the inventory of the product in each target warehouse in the at least one target warehouse, the preset inventory ratio, and the required quantity of the product recorded by the to-be-processed order.
  • the target warehouse stores the number of products to be shipped out of the above products.
  • the current inventory ratio of the above products in each of the target warehouses in the at least one target warehouse may be first determined. Then, the current inventory ratio and the demand quantity of the above-mentioned products recorded in the above-mentioned pending order can be known, and the inventory ratio after the outbound storage of each target warehouse is the same as or similar to the preset inventory ratio, and the solution is solved from each target warehouse.
  • the number of items to be shipped out of the above products are the number of items to be shipped out of the above products.
  • the pushing unit 504 can push information including the determined number of items to be shipped corresponding to each target warehouse.
  • this information can be pushed to a server for managing inventory (e.g., inventory server 102 shown in Figure 1).
  • a server for managing inventory e.g., inventory server 102 shown in Figure 1.
  • the above information may also include the names of the respective target warehouses, the product information of the above products, and the above-mentioned pending orders.
  • the inventory information further includes preset outbound request information.
  • the parsing unit 502 may include a first determining module and a second determining module (not shown).
  • the first determining module may be configured to determine, according to the foregoing outbound request information, a priority of each warehouse in which the product is stored, and determine a weight corresponding to each priority.
  • the second determining module may be configured to establish a mathematical model based on the determined weights and priorities of the respective warehouses, and determine an optimal solution of the mathematical model, and determine each warehouse indicated by the optimal solution as used for delivery The target warehouse for the above products.
  • the foregoing second determining module may include a first determining submodule and a second determining submodule (not shown).
  • the first determining submodule may be configured to determine the number of products of the product involved in the to-be-processed order and the number of solutions of the mathematical model.
  • the second determining sub-module may be configured to determine a solution manner based on the number of products of the product involved in the order to be processed and/or the number of solutions of the mathematical model, and determine the optimality of the mathematical model by using the determined solution manner. solution.
  • the second determining submodule may be further configured to determine an optimal solution of the mathematical model based on a greedy algorithm in response to determining that the number of products is less than a first predetermined number.
  • the second determining submodule may be further configured to: in response to determining that the number of products is not less than the first preset number, and the number of the solutions is less than a second preset quantity, The optimal solution of the above mathematical model is determined based on the constraint programming method.
  • the second determining submodule may be further configured to: responsive to determining that the number of products is not less than the first preset number, and the number of the solutions is not less than the second preset
  • the quantity combined with the above greedy algorithm and the above constraint planning method, determines the optimal solution of the above mathematical model.
  • the device provided by the above embodiment of the present application parses the to-be-processed order and inventory information extracted by the extracting unit 501 by the parsing unit 502 to determine a target warehouse, and then the determining unit 503 is based on the inventory of each warehouse, the preset inventory ratio, and The quantity of products required to determine the number of items to be shipped out of each target warehouse, and finally the pushing unit 504 pushes information including the determined number of items to be released, thereby not only determining the warehouse for the products involved in the delivery order, but also Flexibility to adjust the outbound quantity of each warehouse for the products involved in the outbound order, thus increasing the flexibility of order processing.
  • FIG. 6 a block diagram of a computer system 600 suitable for use in implementing a server of an embodiment of the present application is shown.
  • the server shown in FIG. 6 is merely an example, and should not impose any limitation on the function and scope of use of the embodiments of the present application.
  • computer system 600 includes a central processing unit (CPU) 601 that can be loaded into a program in random access memory (RAM) 603 according to a program stored in read only memory (ROM) 602 or from storage portion 608. And perform various appropriate actions and processes.
  • RAM random access memory
  • ROM read only memory
  • RAM random access memory
  • various programs and data required for the operation of the system 600 are also stored.
  • the CPU 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604.
  • An input/output (I/O) interface 605 is also coupled to bus 604.
  • the following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, etc.; an output portion 607 including, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), and the like, and a storage portion 608 including a hard disk or the like. And a communication portion 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the Internet.
  • Driver 610 is also coupled to I/O interface 605 as needed.
  • a removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory or the like, is mounted on the drive 610 as needed so that a computer program read therefrom is installed into the storage portion 608 as needed.
  • an embodiment of the present disclosure includes a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for executing the method illustrated in the flowchart.
  • the computer program can be downloaded and installed from the network via communication portion 609, and/or installed from removable media 611.
  • the central processing unit (CPU) 601 the above-described functions defined in the method of the present application are performed.
  • the computer readable medium described herein may be a computer readable signal medium or a computer readable storage medium or any combination of the two.
  • the computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of computer readable storage media may include, but are not limited to, electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), erasable Programmable read only memory (EPROM or flash memory), optical fiber, portable compact disk read only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the foregoing.
  • a computer readable storage medium may be any tangible medium that can contain or store a program, which can be used by or in connection with an instruction execution system, apparatus or device.
  • a computer readable signal medium may include a data signal that is propagated in the baseband or as part of a carrier, carrying computer readable program code. Such propagated data signals can take a variety of forms including, but not limited to, electromagnetic signals, optical signals, or any suitable combination of the foregoing.
  • the computer readable signal medium can also be any computer readable medium other than a computer readable storage medium, which can transmit, propagate, or transport a program for use by or in connection with the instruction execution system, apparatus, or device.
  • Program code embodied on a computer readable medium can be transmitted by any suitable medium, including but not limited to wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
  • each block of the flowchart or block diagram can represent a module, a program segment, or a portion of code that includes one or more of the logic functions for implementing the specified.
  • Executable instructions can also occur in a different order than that illustrated in the drawings. For example, two successively represented blocks may in fact be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending upon the functionality involved.
  • each block of the block diagrams and/or flowcharts, and combinations of blocks in the block diagrams and/or flowcharts can be implemented in a dedicated hardware-based system that performs the specified function or operation. Or it can be implemented by a combination of dedicated hardware and computer instructions.
  • the units involved in the embodiments of the present application may be implemented by software or by hardware.
  • the described unit may also be provided in the processor, for example, as a processor including an extracting unit, a parsing unit, a determining unit, and a pushing unit. Wherein, the names of these units do not constitute a limitation on the unit itself under certain circumstances.
  • the extraction unit may also be described as "a unit that extracts inventory information of products to be processed and products involved in the order to be processed".
  • the present application also provides a computer readable medium, which may be included in the apparatus described in the above embodiments, or may be separately present and not incorporated into the apparatus.
  • the computer readable medium carries one or more programs, when the one or more programs are executed by the device, causing the device to: extract the pending order and the inventory information of the product involved in the pending order, wherein
  • the inventory information includes an inventory of each warehouse in which the product is stored and a preset inventory ratio of the product in each warehouse; the pending order and the inventory information are parsed to determine that the warehouse in which the product is stored is used for delivery At least one target warehouse of the product; determining the inventory from each target based on the inventory of the product in each of the target warehouses in the at least one target warehouse, the preset inventory ratio, and the demand quantity of the product recorded by the pending order

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Abstract

本申请公开了信息推送方法和装置。该方法的一具体实施方式包括：提取待处理订单和该待处理订单所涉及的产品的库存信息，其中，该库存信息包括存储有该产品的各个仓库的库存和该产品在各个仓库的预置库存比例；对该待处理订单和该库存信息进行解析，确定存储有该产品的仓库中的、用于出库该产品的至少一个目标仓库；基于该产品在上述至少一个目标仓库中的各个目标仓库中的库存、该预置库存比例和该待处理订单所记录的该产品的需求数量，确定从各个目标仓库出库该产品的待出库数量；推送包含所确定的各个目标仓库所对应的待出库数量的信息。该实施方式提高了订单处理的灵活性。

Description

信息推送方法和装置
相关申请的交叉引用
本专利申请要求于2017年6月29日提交的、申请号为201710517317.6、申请人为北京京东世纪贸易有限公司和北京京东尚科信息技术有限公司、发明名称为“信息推送方法和装置”的中国专利申请的优先权，该申请的全文以引用的方式并入本申请中。
技术领域
本申请涉及计算机技术领域，具体涉及互联网技术领域，尤其涉及信息推送方法和装置。
背景技术
随着计算机技术的发展，电子商务越来越普及。通常，需要依赖若干仓库进行物品存储。用户购买时，可以同时选择任意商品种类以及数量的组合。这些商品可能分别存储在多个仓库，即便订单中只有一种商品，也可能需要多个仓库的库存才能够满足。因而，确定每个订单的目标仓库非常重要。
现有的方式通常是在每次判断时查询库存信息，通过确定不同方案下的优劣进一步筛选，如存在多个相同优劣程度的方案，则进入更细化的判断，直至最终找出唯一的仓库，因而，存在着灵活性较低等问题。
发明内容
本申请实施例的目的在于提出一种改进的信息推送方法和装置，来解决以上背景技术部分提到的技术问题。
第一方面，本申请实施例提供了一种信息推送方法，该方法包括：提取待处理订单和待处理订单所涉及的产品的库存信息，其中，库存 信息包括存储有产品的各个仓库的库存和产品在各个仓库的预置库存比例；对待处理订单和库存信息进行解析，确定存储有产品的仓库中的、用于出库产品的至少一个目标仓库；基于产品在上述至少一个目标仓库中的各个目标仓库中的库存、预置库存比例和待处理订单所记录的产品的需求数量，确定从各个目标仓库出库产品的待出库数量；推送包含所确定的各个目标仓库所对应的待出库数量的信息。
在一些实施例中，库存信息还包括预置的出库要求信息；以及对待处理订单和库存信息进行解析，确定存储有产品的仓库中的、用于出库产品的至少一个目标仓库，包括：基于出库要求信息，确定存储有产品的各个仓库的优先级，并确定各个优先级所对应的权重；基于所确定的权重和各个仓库的优先级，建立数学模型，并确定数学模型的最优解，将最优解所指示的各个仓库确定为用于出库产品的目标仓库。
在一些实施例中，基于所确定的权重和各个仓库的优先级，建立数学模型，并确定数学模型的最优解，包括：确定待处理订单所涉及的产品的产品数量和数学模型的解的数量；基于待处理订单所涉及的产品的产品数量和/或数学模型的解的数量，确定求解方式，并利用确定的求解方式确定数学模型的最优解。
在一些实施例中，基于待处理订单所涉及的产品的产品数量和/或数学模型的解的数量，确定求解方式，并利用确定的求解方式确定数学模型的最优解，包括：响应于确定产品数量小于第一预设数量，基于贪婪算法确定数学模型的最优解。
在一些实施例中，基于待处理订单所涉及的产品的产品数量和/或数学模型的解的数量，确定求解方式，并利用确定的求解方式确定数学模型的最优解，包括：响应于确定产品数量不小于第一预设数量且解的数量小于第二预设数量，基于约束规划方法确定数学模型的最优解。
在一些实施例中，基于待处理订单所涉及的产品的产品数量和/或数学模型的解的数量，确定求解方式，并利用确定的求解方式确定数学模型的最优解，包括：响应于确定产品数量不小于第一预设数量 且解的数量不小于第二预设数量，结合贪婪算法和约束规划方法确定数学模型的最优解。
第二方面，本申请实施例提供了一种信息推送装置，该装置包括：提取单元，配置用于提取待处理订单和待处理订单所涉及的产品的库存信息，其中，库存信息包括存储有产品的各个仓库的库存和产品在各个仓库的预置库存比例；解析单元，配置用于对待处理订单和库存信息进行解析，确定存储有产品的仓库中的、用于出库产品的至少一个目标仓库；确定单元，配置用于基于产品在上述至少一个目标仓库中的各个目标仓库中的库存、预置库存比例和待处理订单所记录的产品的需求数量，确定从各个目标仓库出库产品的待出库数量；推送单元，配置用于推送包含所确定的各个目标仓库所对应的待出库数量的信息。
在一些实施例中，库存信息还包括预置的出库要求信息；以及解析单元包括：第一确定模块，配置用于基于出库要求信息，确定存储有产品的各个仓库的优先级，并确定各个优先级所对应的权重；第二确定模块，配置用于基于所确定的权重和各个仓库的优先级，建立数学模型，并确定数学模型的最优解，将最优解所指示的各个仓库确定为用于出库产品的目标仓库。
在一些实施例中，第二确定模块包括：第一确定子模块，配置用于确定待处理订单所涉及的产品的产品数量和数学模型的解的数量；第二确定子模块，配置用于基于待处理订单所涉及的产品的产品数量和/或数学模型的解的数量，确定求解方式，并利用确定的求解方式确定数学模型的最优解。
在一些实施例中，第二确定子模块进一步配置用于：响应于确定产品数量小于第一预设数量，基于贪婪算法确定数学模型的最优解。
在一些实施例中，第二确定子模块进一步配置用于：响应于确定产品数量不小于第一预设数量且解的数量小于第二预设数量，基于约束规划方法确定数学模型的最优解。
在一些实施例中，第二确定子模块进一步配置用于：响应于确定产品数量不小于第一预设数量且解的数量不小于第二预设数量，结合 贪婪算法和约束规划方法确定数学模型的最优解。
第三方面，本申请实施例提供了一种服务器，包括：一个或多个处理器；存储装置，用于存储一个或多个程序，当一个或多个程序被一个或多个处理器执行，使得一个或多个处理器实现如信息推送方法中任一实施例的方法。
第四方面，本申请实施例提供了一种计算机可读存储介质，其上存储有计算机程序，其特征在于，该程序被处理器执行时实现如信息推送方法中任一实施例的方法。
本申请实施例提供的信息推送方法和装置，通过对所提取的待处理订单和库存信息进行解析，以确定目标仓库，而后基于各个仓库的库存、预置库存比例和产品的需求数量，确定各个目标仓库对应的待出库数量，最后推送包含所确定的待出库数量的信息，从而不仅可以确定用于出库订单中所涉及产品的仓库，还可以灵活调整用于出库订单中所涉及产品的各个仓库的出库数量，从而提高了订单处理的灵活性。
附图说明
通过阅读参照以下附图所作的对非限制性实施例所作的详细描述，本申请的其它特征、目的和优点将会变得更明显：
图1是本申请可以应用于其中的示例性系统架构图；
图2是根据本申请的信息推送方法的一个实施例的流程图；
图3是根据本申请的信息推送方法的一个应用场景的示意图；
图4是根据本申请的信息推送方法的又一个实施例的流程图；
图5是根据本申请的信息推送装置的一个实施例的结构示意图；
图6是适于用来实现本申请实施例的服务器的计算机系统的结构示意图。
具体实施方式
下面结合附图和实施例对本申请作进一步的详细说明。可以理解的是，此处所描述的具体实施例仅仅用于解释相关发明，而非对该发 明的限定。另外还需要说明的是，为了便于描述，附图中仅示出了与有关发明相关的部分。
需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。下面将参考附图并结合实施例来详细说明本申请。
图1示出了可以应用本申请的信息推送方法或信息推送装置的示例性系统架构100。
如图1所示，系统架构100可以包括数据存储服务器101、库存服务器102、网络103和订单处理服务器104。网络103用以数据存储服务器101、库存服务器102和订单处理服务器104之间提供通信链路的介质。网络102可以包括各种连接类型，例如有线、无线通信链路或者光纤电缆等等。
数据存储服务器101中可以存储有各种信息，例如待处理订单、库存信息、各个仓库所存储的产品的信息(例如生产日期、保质期等)、用户设置的出库要求等信息。
库存服务器102可以与各个仓库所部署的终端设备(图中未示出)通信连接，并将各个仓库待出库的产品的信息(可以包括产品编码、产品的待出库数量等)发送至各个仓库所部署的终端设备。其中，仓库管理人员可以通过上述终端设备所显示的信息进行产品的拣选，或向拣选机器人发送指令，使之进行产品的拣选等操作。
订单处理服务器104可以通过网络103分别与数据存储服务器101和库存服务器102交互，以接收或发送消息等。订单处理服务器104可以获取数据存储服务器101所存储的待处理订单、库存信息等，也可以对所获取的信息进行分析等处理，并将处理结果(例如多个仓库待出库的产品及数量等)推送至库存服务器102。
需要说明的是，上述订单处理服务器104也可以具备数据存储服务器101和库存服务器102的功能，此时，系统架构100可以不包含数据存储服务器101和库存服务器102。
需要说明的是，本申请实施例所提供的信息推送方法一般由服务器104执行，相应地，信息推送装置一般设置于服务器104中。
应该理解，图1中的终端设备、网络和服务器的数目仅仅是示意性的。根据实现需要，可以具有任意数目的数据存储服务器、库存服务器、网络和订单处理服务器。
继续参考图2，示出了根据本申请的信息推送方法的一个实施例的流程200。所述的信息推送方法，包括以下步骤：
步骤201，提取待处理订单和待处理订单所涉及的产品的库存信息。
在本实施例中，信息推送方法运行与其上的电子设备(例如图1所示的订单处理服务器104)可以提取待处理订单和待处理订单所涉及的产品的库存信息。其中，上述待处理订单可以是未确定产品待出库的仓库的订单。上述待处理订单所涉及的产品的库存信息可以包括存储有上述产品的各个仓库的库存(此处指库存量)和上述产品各个仓库的预置库存比例。作为示例，某个产品在第一仓库、第二仓库和第三仓库有库存，且在上述第一仓库、上述第二仓库和上述第三仓库的预置库存比例为8:1:1。
需要说明的是，上述待处理订单和待处理订单所涉及的产品的库存信息可以预先存储在上述电子设备中，此时，上述电子设备可以直接从本地提取上述待处理订单和上述库存信息。另外，上述待处理订单和上述库存信息也可以存储在另一服务器(例如图1所示的数据存储服务器101)中，此时，上述电子设备可以通过有线连接方式或者无线连接方式从该服务器中提取上述待处理订单和上述库存信息。实践中，网址一般由统一资源定位符(Uniform Resource Locator，URL)来表示。需要指出的是，上述无线连接方式可以包括但不限于3G/4G连接、WiFi连接、蓝牙连接、WiMAX连接、Zigbee连接、UWB(ultra wideband)连接、以及其他现在已知或将来开发的无线连接方式。
步骤202，对待处理订单和库存信息进行解析，确定存储有上述产品的仓库中的、用于出库上述产品的至少一个目标仓库。
在本实施例中，上述电子设备可以利用各种分析方式对上述待处理订单和上述库存信息进行解析，确定存储有上述产品的仓库中的、 用于出库上述产品的至少一个目标仓库。作为示例，上述电子设备可以确定存储有上述待处理订单所涉及的产品的仓库中是否存在能满足上述待处理订单的产品需求的仓库，若存在，则将满足需求的仓库中的、与待处理订单所记载的配送地址距离最近的仓库确定为目标仓库；若不存在，则将存储有上述待处理订单所涉及的产品的仓库中的两个仓库进行结合，确定是否存在能满足上述待处理订单的产品需求的一组仓库，若存在，选取需求的其中一组仓库，将所选取的仓库确定为目标仓库，若不存在，则将存储有上述待处理订单所涉及的产品的仓库中的三个仓库进行结合，以此类推，直至确定出用于出库上述产品的至少一个目标仓库。
步骤203，基于上述产品在上述至少一个目标仓库中的各个目标仓库中的库存、预置库存比例和待处理订单所记录的上述产品的需求数量，确定从各个目标仓库出库上述产品的待出库数量。
在本实施例中，上述电子设备可以基于上述产品在上述至少一个目标仓库中的各个目标仓库中的库存、预置库存比例和上述待处理订单所记录的上述产品的需求数量，确定从各个目标仓库出库上述产品的待出库数量。具体地，上述电子设备可以首先确定上述产品在上述至少一个目标仓库中的各个目标仓库中的当前库存比例。而后，上述电子设备可以已知上述当前库存比例和上述待处理订单所记录的上述产品的需求数量，以各个目标仓库出库后的库存比例与预置库存比例相同或相近为条件，解出从各个目标仓库出库上述产品的待出库数量。作为示例，某个产品在第一仓库、第二仓库和第三仓库有库存，且在上述第一仓库、上述第二仓库和上述第三仓库的预置库存比例为2:2:1，上述第一仓库、上述第二仓库和上述第三仓库的中的该产品的库存分别为30、10、10，即当前库存比例为3:1:1，若该产品的需求数量为30，则上述第一仓库对应的待出库数量为22，上述第二仓库对应的待出库数量为2，上述第三仓库对应的待出库数量为6。
步骤204，推送包含所确定的各个目标仓库所对应的待出库数量的信息。
在本实施例中，上述电子设备可以推送包含所确定的各个目标仓 库所对应的待出库数量的信息。实践中，上述电子设备可以将该信息推送至用于管理库存的服务器(例如图1所示的库存服务器102)。需要说明的是，上述信息中还可以包括各个目标仓库的名称、上述产品的产品信息和上述待处理订单等。
继续参见图3，图3是根据本实施例的信息推送方法的应用场景的一个示意图。在图3的应用场景中，订单处理服务器301可以首先从数据存储服务器302中提取待处理订单303和上述待处理订单所涉及的产品的库存信息304，且该库存信息304中包含上述产品在各个仓库的预置库存比例。而后，订单处理服务器301可以对待处理订单303和库存信息304进行解析至少一个目标仓库305。之后。订单处理服务器301可以基于上述产品在各个目标仓库中的库存、预置库存比例和待处理订单所记录的上述产品的需求数量，确定从各个目标仓库出库上述产品的待出库数量306。最后，订单处理服务器301可以推送包含所确定的各个目标仓库所对应的待出库数量306的信息307至库存服务器308。
本申请的上述实施例提供的方法，通过本申请实施例提供的信息推送方法和装置，通过对所提取的待处理订单和库存信息进行解析，以确定目标仓库，而后基于各个仓库的库存、预置库存比例和产品的需求数量，确定各个目标仓库对应的待出库数量，最后推送包含所确定的待出库数量的信息，从而不仅可以确定用于出库订单中所涉及产品的仓库，还可以灵活调整用于出库订单中所涉及产品的各个仓库的出库数量，从而提高了订单处理的灵活性。
进一步参考图4，其示出了信息推送方法的又一个实施例的流程400。该信息推送方法的流程400，包括以下步骤：
步骤401，提取待处理订单和待处理订单所涉及的产品的库存信息。
在本实施例中，信息推送方法运行与其上的电子设备(例如图1所示的订单处理服务器104)可以提取待处理订单和待处理订单所涉 及的产品的库存信息。其中，上述待处理订单可以是未确定产品待出库的仓库的订单。上述待处理订单所涉及的产品的库存信息可以包括存储有上述产品的各个仓库的库存和上述产品各个仓库的预置库存比例。
步骤402，基于出库要求信息，确定存储有上述产品的各个仓库的优先级，并确定各个优先级所对应的权重。
在本实施例中，上述库存信息还可以包括预置的出库要求信息。例如，上述出库要求可以包括但不限于接近保质期的产品优先出库、某一仓库所存储的产品优先出库等。上述电子设备可以首先基于上述出库要求信息，确定存储有上述产品的各个仓库的优先级，并确定各个优先级所对应的权重。作为示例，可以将仓库的优先级划分为三个等级，从高到低分别为第一优先级(例如，某个仓库中存储的上述产品接近保质期，则可以确定该仓库的优先级为第一优先级)、第二优先级(例如，上述产品在某个仓库的实际库存比例大于预置库存比例，则可以确定该仓库的优先级为第二优先级)和第三优先级(例如，可以将除上述第一优先级和第二优先级外的其余仓库的优先级确定为第三优先级)。此处，各个优先级对应的权重可以是技术人员预先设置的任意数值(例如0.2、0.5或0.8等)。
步骤403，基于所确定的权重和各个仓库的优先级，建立数学模型，并确定数学模型的最优解，将最优解所指示的各个仓库确定为用于出库上述产品的目标仓库。
在本实施例中，在确定各个优先级所对应的权重之后，上述电子设备可以基于所确定的权重和各个仓库的优先级，建立数学模型。作为示例，上述电子设备可以通过以下步骤建立数学模型：
第一步，可以设置变量J SW和I W，并设立约束条件I W≥J SW。其中，S表示上述待处理订单所涉及的任一产品S，W表示存储有上述待处理订单所涉及的产品的任一仓库，J SW可以是1或0，用以表示产品S是否在仓库W出库。当J SW为1时，表示产品S在仓库W出库；当J SW为0时，表示产品S不在仓库W出库。I W可以是1或0，用以表示仓库W是否出库上述待处理订单所涉及的产品中的至少一种产品，即仓 库W是否被使用。当I W为1时，表示仓库W被使用；当I W为0时，表示仓库W未被使用。上述约束条件I W≥J SW表示如果产品S在仓库W出库，则仓库W被使用。
第二步，可以基于存储有上述待处理订单所涉及的每一种产品的仓库的优先级和每一种优先级的权重，建立如下的数学模型：
Figure PCTCN2018083373-appb-000001
其中，上述P 1、P 2、P 3分别表示存储有上述待处理订单所涉及的任一产品S的第一优先级的仓库的集合、存储有上述待处理订单所涉及的任一产品S的第二优先级的仓库的集合、存储有上述待处理订单所涉及的任一产品S的第三优先级的仓库的集合；上述W 1、W 2、W 3分别表示第一优先级对应的权重、第二优先级对应的权重、第三优先级对应的权重；上述W 0用于表示被使用的仓库的总数的权重，上述W 0可以是技术人员基于大量数据统计和计算而预先设置的、分别大于W 1、W 2和W 3的任意数值。
上述电子设备还可以建立上述数学模型的约束条件：
Figure PCTCN2018083373-appb-000002
Figure PCTCN2018083373-appb-000003
其中，上述q SW为仓库W中的产品S的库存；d S为上述待处理订单中产品S的需求数量。
在本实施例中，上述电子设备可以利用各种求解方式(例如贪婪算法等启发式算法，以及约束规划和整数规划等精确求解方法)确定上述数学模型的最优解，将最优解所指示的各个仓库确定为用于出库上述产品的目标仓库。其中，上述最优解即上述数学模型的最小值时各个J SW和I W的取值。此外，上述电子设备还可以解出I W之和的最小值，即最小使用仓库总数。
在本实施例的一些可选的实现方式中，上述电子设备可以首先确定上述待处理订单所涉及的产品的产品数量(指产品的种类的数量)和上述数学模型的解的数量；而后，可以基于上述待处理订单所涉及的产品的产品数量和/或上述数学模型的解的数量，确定求解方式，并 利用所确定的求解方式确定上述数学模型的最优解。
在本实施例的一些可选的实现方式中，响应于确定上述产品数量小于第一预设数量(例如5个)，上述电子设备可以基于贪婪算法确定上述数学模型的最优解。实践中，贪婪算法(又称贪心算法)是指在对问题求解时，总是做出在当前看来是最好的选择。也就是说，不从整体最优上加以考虑，他所做出的是在某种意义上的局部最优解。上述电子可以直接将使用贪婪算法得到的上述局部最优解确定为上述数学模型的最优解。需要说明的是，由于利用贪婪算法求解上述数学模型用于产品数量小于第一预设数量的情况下，即产品数量较小的情况下，因此，使用贪婪算法得到的上述局部最优解通常是上述数学模型的最优解或与最优解较为接近的解，因而准确率较高。
在本实施例的一些可选的实现方式中，响应于确定上述产品数量不小于上述第一预设数量且上述解的数量小于第二预设数量(例如十万个)，上述电子设备可以基于约束规划方法确定上述数学模型的最优解。实践中，约束规划(Constraint programming)是一种研究基于约束的组合优化问题的计算技术，可以利用高效的约束传播和搜索机制迅速得到问题的可行解，进而确定最优解。其中，上述约束传播又称一致性检查或预处理技术，用于回答问题是否具有可行解；上述搜索机制通常采用树搜索算法以深度优先搜索的方式，通过不断搜索下一个要赋值的变量和实验性地为所选的变量赋值来构造问题解，若有约束冲突发生，则通过回溯取消一个或几个更早赋值的变量值，重新为该变量选择一个值。在约束规划方法中，变量之间的关系是以约束的形式组织的。这些约束和命令式编程语言元素不同的是，它们并非明确说明了要去执行的步骤中的某一步，而是规范其解的一些属性。因而，可以利用约束规划方法进行上述数学模型的求解，并得到最优解。
在本实施例的一些可选的实现方式中，响应于确定上述产品数量不小于上述第一预设数量且上述解的数量不小于上述第二预设数量，上述电子设备可以结合上述贪婪算法和上述约束规划方法确定上述数学模型的最优解。具体地，可以先通过约束规划方法确定最小使用仓库总数，而后，再利用贪婪算法确定在满足最小使用仓库总数的情况 下的最优解，即各个J SW和I W的取值。
需要说明的是，上述贪婪算法、约束规划方法是在目前求解数学模型的过程中广泛研究和应用的公知技术，在此不再赘述。
步骤404，基于上述产品在上述至少一个目标仓库中的各个目标仓库中的库存、预置库存比例和待处理订单所记录的上述产品的需求数量，确定从各个目标仓库出库上述产品的待出库数量。
在本实施例中，上述电子设备可以基于上述产品在上述至少一个目标仓库中的各个目标仓库中的库存、预置库存比例和上述待处理订单所记录的上述产品的需求数量，确定从各个目标仓库出库上述产品的待出库数量。具体地，上述电子设备可以首先确定上述产品在上述至少一个目标仓库中的各个目标仓库中的当前库存比例。而后，上述电子设备可以已知上述当前库存比例和上述待处理订单所记录的上述产品的需求数量，以各个目标仓库出库后的库存比例与预置库存比例相同或相近为条件，解出从各个目标仓库出库上述产品的待出库数量。
步骤405，推送包含所确定的各个目标仓库所对应的待出库数量的信息。
在本实施例中，上述电子设备可以推送包含所确定的各个目标仓库所对应的待出库数量的信息。实践中，上述电子设备可以将该信息推送至用于管理库存的服务器(例如图1所示的库存服务器102)。需要说明的是，上述信息中还可以包括各个目标仓库的名称、上述产品的产品信息和上述待处理订单等。
需要指出的是，上述步骤401、步骤404、步骤405的操作与上述步骤201、步骤203、步骤205的操作基本相同，在此不再赘述。
从图4中可以看出，与图2对应的实施例相比，本实施例中的信息推送方法的流程400突出了通过建立数学模型并使用不同算法求最优解来确定目标仓库的步骤。由此，本实施例描述的方案可以针对订单的复杂程度使用不同算法确定最优解指示的目标仓库，不仅可以降低使订单的生产成本，还可以提高订单的处理效率。
进一步参考图5，作为对上述各图所示方法的实现，本申请提供 了一种信息推送装置的一个实施例，该装置实施例与图2所示的方法实施例相对应，该装置具体可以应用于各种电子设备中。
如图5所示，本实施例所述的信息推送装置500包括：提取单元501，配置用于提取待处理订单和上述待处理订单所涉及的产品的库存信息，其中，上述库存信息包括存储有上述产品的各个仓库的库存和上述产品在各个仓库的预置库存比例；解析单元502，配置用于对上述待处理订单和上述库存信息进行解析，确定存储有上述产品的仓库中的、用于出库上述产品的至少一个目标仓库；确定单元503，配置用于基于上述产品在上述至少一个目标仓库中的各个目标仓库中的库存、上述预置库存比例和上述待处理订单所记录的上述产品的需求数量，确定从各个目标仓库出库上述产品的待出库数量；推送单元504，配置用于推送包含所确定的各个目标仓库所对应的待出库数量的信息。
在本实施例中，上述提取单元501可以提取待处理订单和待处理订单所涉及的产品的库存信息。其中，上述待处理订单可以是未确定产品待出库的仓库的订单。上述待处理订单所涉及的产品的库存信息可以包括存储有上述产品的各个仓库的库存和上述产品各个仓库的预置库存比例。
在本实施例中，上述解析单元502可以利用各种分析方式对上述待处理订单和上述库存信息进行解析，确定存储有上述产品的仓库中的、用于出库上述产品的至少一个目标仓库。
在本实施例中，上述确定单元503可以基于上述产品在上述至少一个目标仓库中的各个目标仓库中的库存、预置库存比例和上述待处理订单所记录的上述产品的需求数量，确定从各个目标仓库出库上述产品的待出库数量。具体地，可以首先确定上述产品在上述至少一个目标仓库中的各个目标仓库中的当前库存比例。而后，可以已知上述当前库存比例和上述待处理订单所记录的上述产品的需求数量，以各个目标仓库出库后的库存比例与预置库存比例相同或相近为条件，解出从各个目标仓库出库上述产品的待出库数量。
在本实施例中，上述推送单元504可以推送包含所确定的各个目 标仓库所对应的待出库数量的信息。实践中，可以将该信息推送至用于管理库存的服务器(例如图1所示的库存服务器102)。需要说明的是，上述信息中还可以包括各个目标仓库的名称、上述产品的产品信息和上述待处理订单等。
在本实施例的一些可选的实现方式中，上述库存信息还包括预置的出库要求信息。上述解析单元502可以包括第一确定模块和第二确定模块(图中未示出)。其中，上述第一确定模块可以配置用于基于上述出库要求信息，确定存储有上述产品的各个仓库的优先级，并确定各个优先级所对应的权重。上述第二确定模块可以配置用于基于所确定的权重和各个仓库的优先级，建立数学模型，并确定上述数学模型的最优解，将最优解所指示的各个仓库确定为用于出库上述产品的目标仓库。
在本实施例的一些可选的实现方式中，上述第二确定模块可以包括第一确定子模块和第二确定子模块(图中未示出)。其中，上述第一确定子模块可以配置用于确定上述待处理订单所涉及的产品的产品数量和上述数学模型的解的数量。上述第二确定子模块可以配置用于基于上述待处理订单所涉及的产品的产品数量和/或上述数学模型的解的数量，确定求解方式，并利用确定的求解方式确定上述数学模型的最优解。
在本实施例的一些可选的实现方式中，上述第二确定子模块可以进一步配置用于响应于确定上述产品数量小于第一预设数量，基于贪婪算法确定上述数学模型的最优解。
在本实施例的一些可选的实现方式中，上述第二确定子模块可以进一步配置用于响应于确定上述产品数量不小于上述第一预设数量且上述解的数量小于第二预设数量，基于约束规划方法确定上述数学模型的最优解。
在本实施例的一些可选的实现方式中，上述第二确定子模块可以进一步配置用于响应于确定上述产品数量不小于上述第一预设数量且上述解的数量不小于上述第二预设数量，结合上述贪婪算法和上述约束规划方法确定上述数学模型的最优解。
本申请的上述实施例提供的装置，通过解析单元502对提取单元501所提取的待处理订单和库存信息进行解析，以确定目标仓库，而后确定单元503基于各个仓库的库存、预置库存比例和产品的需求数量，确定各个目标仓库对应的待出库数量，最后推送单元504推送包含所确定的待出库数量的信息，从而不仅可以确定用于出库订单中所涉及产品的仓库，还可以灵活调整用于出库订单中所涉及产品的各个仓库的出库数量，从而提高了订单处理的灵活性。
下面参考图6，其示出了适于用来实现本申请实施例的服务器的计算机系统600的结构示意图。图6示出的服务器仅仅是一个示例，不应对本申请实施例的功能和使用范围带来任何限制。
如图6所示，计算机系统600包括中央处理单元(CPU)601，其可以根据存储在只读存储器(ROM)602中的程序或者从存储部分608加载到随机访问存储器(RAM)603中的程序而执行各种适当的动作和处理。在RAM 603中，还存储有系统600操作所需的各种程序和数据。CPU 601、ROM 602以及RAM 603通过总线604彼此相连。输入/输出(I/O)接口605也连接至总线604。
以下部件连接至I/O接口605：包括键盘、鼠标等的输入部分606；包括诸如阴极射线管(CRT)、液晶显示器(LCD)等以及扬声器等的输出部分607；包括硬盘等的存储部分608；以及包括诸如LAN卡、调制解调器等的网络接口卡的通信部分609。通信部分609经由诸如因特网的网络执行通信处理。驱动器610也根据需要连接至I/O接口605。可拆卸介质611，诸如磁盘、光盘、磁光盘、半导体存储器等等，根据需要安装在驱动器610上，以便于从其上读出的计算机程序根据需要被安装入存储部分608。
特别地，根据本公开的实施例，上文参考流程图描述的过程可以被实现为计算机软件程序。例如，本公开的实施例包括一种计算机程序产品，其包括承载在计算机可读介质上的计算机程序，该计算机程序包含用于执行流程图所示的方法的程序代码。在这样的实施例中，该计算机程序可以通过通信部分609从网络上被下载和安装，和/或从 可拆卸介质611被安装。在该计算机程序被中央处理单元(CPU)601执行时，执行本申请的方法中限定的上述功能。需要说明的是，本申请所述的计算机可读介质可以是计算机可读信号介质或者计算机可读存储介质或者是上述两者的任意组合。计算机可读存储介质例如可以是——但不限于——电、磁、光、电磁、红外线、或半导体的系统、装置或器件，或者任意以上的组合。计算机可读存储介质的更具体的例子可以包括但不限于：具有一个或多个导线的电连接、便携式计算机磁盘、硬盘、随机访问存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、光纤、便携式紧凑磁盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。在本申请中，计算机可读存储介质可以是任何包含或存储程序的有形介质，该程序可以被指令执行系统、装置或者器件使用或者与其结合使用。而在本申请中，计算机可读的信号介质可以包括在基带中或者作为载波一部分传播的数据信号，其中承载了计算机可读的程序代码。这种传播的数据信号可以采用多种形式，包括但不限于电磁信号、光信号或上述的任意合适的组合。计算机可读的信号介质还可以是计算机可读存储介质以外的任何计算机可读介质，该计算机可读介质可以发送、传播或者传输用于由指令执行系统、装置或者器件使用或者与其结合使用的程序。计算机可读介质上包含的程序代码可以用任何适当的介质传输，包括但不限于：无线、电线、光缆、RF等等，或者上述的任意合适的组合。
附图中的流程图和框图，图示了按照本申请各种实施例的系统、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段、或代码的一部分，该模块、程序段、或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个接连地表示的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是， 框图和/或流程图中的每个方框、以及框图和/或流程图中的方框的组合，可以用执行规定的功能或操作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。
描述于本申请实施例中所涉及到的单元可以通过软件的方式实现，也可以通过硬件的方式来实现。所描述的单元也可以设置在处理器中，例如，可以描述为：一种处理器包括提取单元、解析单元、确定单元和推送单元。其中，这些单元的名称在某种情况下并不构成对该单元本身的限定，例如，提取单元还可以被描述为“提取待处理订单和待处理订单所涉及的产品的库存信息的单元”。
作为另一方面，本申请还提供了一种计算机可读介质，该计算机可读介质可以是上述实施例中描述的装置中所包含的；也可以是单独存在，而未装配入该装置中。上述计算机可读介质承载有一个或者多个程序，当上述一个或者多个程序被该装置执行时，使得该装置：提取待处理订单和该待处理订单所涉及的产品的库存信息，其中，该库存信息包括存储有该产品的各个仓库的库存和该产品在各个仓库的预置库存比例；对该待处理订单和该库存信息进行解析，确定存储有该产品的仓库中的、用于出库该产品的至少一个目标仓库；基于该产品在上述至少一个目标仓库中的各个目标仓库中的库存、该预置库存比例和该待处理订单所记录的该产品的需求数量，确定从各个目标仓库出库该产品的待出库数量；推送包含所确定的各个目标仓库所对应的待出库数量的信息。
以上描述仅为本申请的较佳实施例以及对所运用技术原理的说明。本领域技术人员应当理解，本申请中所涉及的发明范围，并不限于上述技术特征的特定组合而成的技术方案，同时也应涵盖在不脱离上述发明构思的情况下，由上述技术特征或其等同特征进行任意组合而形成的其它技术方案。例如上述特征与本申请中公开的(但不限于)具有类似功能的技术特征进行互相替换而形成的技术方案。

Claims (14)

  1. 一种信息推送方法，其特征在于，所述方法包括：
    提取待处理订单和所述待处理订单所涉及的产品的库存信息，其中，所述库存信息包括存储有所述产品的各个仓库的库存和所述产品在各个仓库的预置库存比例；
    对所述待处理订单和所述库存信息进行解析，确定存储有所述产品的仓库中的、用于出库所述产品的至少一个目标仓库；
    基于所述产品在上述至少一个目标仓库中的各个目标仓库中的库存、所述预置库存比例和所述待处理订单所记录的所述产品的需求数量，确定从各个目标仓库出库所述产品的待出库数量；
    推送包含所确定的各个目标仓库所对应的待出库数量的信息。
  2. 根据权利要求1所述的信息推送方法，其特征在于，所述库存信息还包括预置的出库要求信息；以及
    所述对所述待处理订单和所述库存信息进行解析，确定存储有所述产品的仓库中的、用于出库所述产品的至少一个目标仓库，包括：
    基于所述出库要求信息，确定存储有所述产品的各个仓库的优先级，并确定各个优先级所对应的权重；
    基于所确定的权重和各个仓库的优先级，建立数学模型，并确定所述数学模型的最优解，将最优解所指示的各个仓库确定为用于出库所述产品的目标仓库。
  3. 根据权利要求2所述的信息推送方法，其特征在于，所述基于所确定的权重和各个仓库的优先级，建立数学模型，并确定所述数学模型的最优解，包括：
    确定所述待处理订单所涉及的产品的产品数量和所述数学模型的解的数量；
    基于所述待处理订单所涉及的产品的产品数量和/或所述数学模 型的解的数量，确定求解方式，并利用确定的求解方式确定所述数学模型的最优解。
  4. 根据权利要求3所述的信息推送方法，其特征在于，所述基于所述待处理订单所涉及的产品的产品数量和/或所述数学模型的解的数量，确定求解方式，并利用确定的求解方式确定所述数学模型的最优解，包括：
    响应于确定所述产品数量小于第一预设数量，基于贪婪算法确定所述数学模型的最优解。
  5. 根据权利要求3所述的信息推送方法，其特征在于，所述基于所述待处理订单所涉及的产品的产品数量和/或所述数学模型的解的数量，确定求解方式，并利用确定的求解方式确定所述数学模型的最优解，包括：
    响应于确定所述产品数量不小于所述第一预设数量且所述解的数量小于第二预设数量，基于约束规划方法确定所述数学模型的最优解。
  6. 根据权利要求3所述的信息推送方法，其特征在于，所述基于所述待处理订单所涉及的产品的产品数量和/或所述数学模型的解的数量，确定求解方式，并利用确定的求解方式确定所述数学模型的最优解，包括：
    响应于确定所述产品数量不小于所述第一预设数量且所述解的数量不小于所述第二预设数量，结合贪婪算法和约束规划方法确定所述数学模型的最优解。
  7. 一种信息推送装置，其特征在于，所述装置包括：
    提取单元，配置用于提取待处理订单和所述待处理订单所涉及的产品的库存信息，其中，所述库存信息包括存储有所述产品的各个仓库的库存和所述产品在各个仓库的预置库存比例；
    解析单元，配置用于对所述待处理订单和所述库存信息进行解析， 确定存储有所述产品的仓库中的、用于出库所述产品的至少一个目标仓库；
    确定单元，配置用于基于所述产品在上述至少一个目标仓库中的各个目标仓库中的库存、所述预置库存比例和所述待处理订单所记录的所述产品的需求数量，确定从各个目标仓库出库所述产品的待出库数量；
    推送单元，配置用于推送包含所确定的各个目标仓库所对应的待出库数量的信息。
  8. 根据权利要求7所述的信息推送装置，其特征在于，所述库存信息还包括预置的出库要求信息；以及
    所述解析单元包括：
    第一确定模块，配置用于基于所述出库要求信息，确定存储有所述产品的各个仓库的优先级，并确定各个优先级所对应的权重；
    第二确定模块，配置用于基于所确定的权重和各个仓库的优先级，建立数学模型，并确定所述数学模型的最优解，将最优解所指示的各个仓库确定为用于出库所述产品的目标仓库。
  9. 根据权利要求8所述的信息推送装置，其特征在于，所述第二确定模块包括：
    第一确定子模块，配置用于确定所述待处理订单所涉及的产品的产品数量和所述数学模型的解的数量；
    第二确定子模块，配置用于基于所述待处理订单所涉及的产品的产品数量和/或所述数学模型的解的数量，确定求解方式，并利用确定的求解方式确定所述数学模型的最优解。
  10. 根据权利要求9所述的信息推送装置，其特征在于，所述第二确定子模块进一步配置用于：
    响应于确定所述产品数量小于第一预设数量，基于贪婪算法确定所述数学模型的最优解。
  11. 根据权利要求9所述的信息推送装置，其特征在于，所述第二确定子模块进一步配置用于：
    响应于确定所述产品数量不小于所述第一预设数量且所述解的数量小于第二预设数量，基于约束规划方法确定所述数学模型的最优解。
  12. 根据权利要求9所述的信息推送装置，其特征在于，所述第二确定子模块进一步配置用于：
    响应于确定所述产品数量不小于所述第一预设数量且所述解的数量不小于所述第二预设数量，结合贪婪算法和约束规划方法确定所述数学模型的最优解。
  13. 一种服务器，包括：
    一个或多个处理器；
    存储装置，用于存储一个或多个程序，
    当所述一个或多个程序被所述一个或多个处理器执行，使得所述一个或多个处理器实现如权利要求1-6中任一所述的方法。
  14. 一种计算机可读存储介质，其上存储有计算机程序，其特征在于，该程序被处理器执行时实现如权利要求1-6中任一所述的方法。
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