WO2021218553A1 - 基于机器人的网状供应链决策方法、设备及存储介质 - Google Patents

基于机器人的网状供应链决策方法、设备及存储介质 Download PDF

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WO2021218553A1
WO2021218553A1 PCT/CN2021/084526 CN2021084526W WO2021218553A1 WO 2021218553 A1 WO2021218553 A1 WO 2021218553A1 CN 2021084526 W CN2021084526 W CN 2021084526W WO 2021218553 A1 WO2021218553 A1 WO 2021218553A1
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information
supply chain
seller
robot
supplier
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PCT/CN2021/084526
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English (en)
French (fr)
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杨志钦
孙雪娟
郑晓琨
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炬星科技（深圳）有限公司
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Publication of WO2021218553A1 publication Critical patent/WO2021218553A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/067—Enterprise or organisation modelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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

Definitions

  • the present invention relates to the field of logistics technology, in particular to a robot-based network supply chain decision-making method, equipment and storage medium.
  • the traditional supply chain usually refers to the entire management chain of manufacturing, purchasing, storage, shipping, and distribution.
  • this traditional supply chain the flow of information, logistics, and capital flows continuously along this supply chain. Since in each link of the above-mentioned traditional supply chain, there will be a large number of middlemen, etc., at the same time, supply chain personnel also need to deal with different sources of information at the same time. For example, for a purchaser, there will be manufacturers and various suppliers in the upstream.
  • the purchaser needs to connect to multiple channels and needs to process a large amount of information at the same time every day; however, due to the lag in the acquisition of some information, Inaccuracy and other issues, the above-mentioned information obtained may be inaccurate and untimely, and the decision made by purchasing personnel based on the above-mentioned inaccurate and untimely information may greatly reduce the overall efficiency of the supply chain. , Increase transaction costs.
  • the invention provides a robot-based network supply chain decision-making method, equipment and storage medium, and aims to provide a technical solution for intelligent supply and demand matching in a network supply chain.
  • the present invention provides a robot-based network supply chain decision-making method, including:
  • the present invention provides a robot-based networked supply chain decision-making platform, which includes a model building module and an intelligent matching module.
  • the model establishment module is used to analyze the operation efficiency of the robots corresponding to the suppliers and the sellers respectively, and establish a storage capacity evaluation model based on the operation of the robots.
  • the intelligent matching module is used to: obtain transaction record information corresponding to the seller, dynamically evaluate and predict the replenishment information corresponding to the seller based on the storage capacity evaluation model; at the same time, obtain the capacity information corresponding to the supplier;
  • the transaction record information and replenishment information corresponding to the seller and the capacity information corresponding to the supplier are intelligently matched with the corresponding supplier and seller based on the corresponding storage capacity evaluation model.
  • the present invention provides an electronic device that includes a memory and a processor, and a robot-based network supply chain decision-making program that can be run on the processor is stored in the memory.
  • the network supply chain decision-making program is run by the processor, the robot-based network supply chain decision-making method is executed.
  • the present invention provides a computer storage medium on which a robot-based network supply chain decision-making program is stored, and the network supply chain decision-making program can be executed by one or more processors to Steps to implement the described robot-based network supply chain decision-making method.
  • the present invention is a cross-platform evaluation table analysis method, equipment and storage medium, analyzes the operating efficiency of the robots corresponding to the suppliers and the sellers respectively, establishes a storage capacity evaluation model based on the operation of the robots; obtains the corresponding information of the sellers Transaction record information, based on the storage capacity evaluation model, dynamically evaluate and predict the replenishment information corresponding to the seller; at the same time, obtain the capacity information corresponding to the supplier; combine the transaction record information and replenishment information corresponding to the seller As well as the capacity information corresponding to the supplier, based on the corresponding warehousing capacity evaluation model, the corresponding supplier and seller are intelligently matched; real-time visualization and rapid response of the entire supply chain are realized, and transportation in the supply chain is reduced. Costs, inventory costs, etc., and the use of robot operations also greatly reduces personnel's daily planning and management work, and improves the user's warehousing service level.
  • Fig. 1 is a schematic diagram of an embodiment of the network supply chain in the robot-based network supply chain decision-making method of the present invention.
  • Figure 2 is a schematic diagram of the traditional supply chain model.
  • Fig. 3 is a schematic flowchart of an embodiment of the robot-based network supply chain decision-making method of the present invention.
  • Fig. 4 is a schematic diagram of an embodiment of a multi-level supply chain in the robot-based network supply chain decision-making method of the present invention.
  • Fig. 5 is a schematic diagram of functional modules of an embodiment of the robot-based network supply chain decision-making device of the present invention.
  • FIG. 6 is a schematic diagram of the internal structure of an embodiment of the electronic device of the present invention.
  • the present invention provides a robot-based method, equipment and storage medium for decision-making in a networked supply chain.
  • the solution provides a networked supply chain decision-making platform, which provides a data communication, sharing and decision-making reference for each link of the supply chain. Platform.
  • Fig. 1 is a schematic diagram of an embodiment of the network supply chain in the robot-based network supply chain decision-making method of the present invention.
  • sellers can publish demands on the networked supply chain platform, such as describing their own demand categories, demand quantities, and other demand information.
  • suppliers will also release a series of production capacity information such as their own production capacity and pricing on the networked supply chain decision-making platform.
  • the networked supply chain decision-making platform will provide information on the supply chain based on the seller’s historical sales volume and current season sales data.
  • the sources of goods are compared, and the corresponding warehousing capacity evaluation model is created for evaluation based on the corresponding situation of the sellers, and the sellers are directly provided with the supplier information containing the best source price and quantity information, and the sellers can be based on the mesh
  • the above-mentioned supplier information provided by the supply chain decision-making platform is used to select and make the final decision.
  • the networked supply chain decision-making platform will also provide suppliers with corresponding production suggestions, and quickly transmit production demand information in the networked supply chain.
  • the network supply chain Compared with the traditional chain supply chain, the network supply chain combines all suppliers and sellers, such as purchasers, into a network of relationships, and transmits all supply and demand information through the network. At the same time, it is calculated by establishing a storage capacity evaluation model, and can be combined with big data forecasts to balance supply and demand, and maximize the benefits of all parties.
  • buyers of sellers can obtain better procurement cycle, purchase quantity and purchase price, and suppliers will also get better production quantity and production cycle. Both supply and demand parties can supply from the network.
  • the cost has been optimized in the chain. In this way, compared with the traditional supply chain model shown in Figure 2, the robot-based network supply chain provided by the present invention can reduce the transaction cost of the supply chain, improve the operating efficiency of the supply chain, and reduce information delays and information failures. Loss caused by accuracy.
  • the robot-based network supply chain decision-making method, equipment, and storage medium provided by the present invention incorporate the relevant data of the robot runtime, make full use of the large amount of execution data generated during the robot running process, and then according to the robot runtime
  • the generated execution data feeds back the upstream business operations in the networked supply chain decision-making platform, so that the upstream and downstream data of the networked supply chain are integrated and connected, and the robot's operating data is integrated into the decision-making process, which also enables the formulation of decision-making plans. Be more intelligent and objective.
  • Fig. 3 is a schematic flow chart of an embodiment of the robot-based network supply chain decision-making method of the present invention.
  • the robot-based network supply chain decision-making method includes steps S10-S30.
  • Step S10 Analyze the operating efficiency of the respective robots of the supplier and the seller, and establish a storage capacity evaluation model based on the operation of the robot.
  • suppliers and sellers perform operations such as transportation, sorting, and loading of goods based on robots.
  • the networked supply chain decision-making platform analyzes the operating efficiency of the robots corresponding to suppliers and sellers, including but not limited to: robot picking efficiency, shelf efficiency, peak information and low peak information of the robot's daily operation; among them, peak Information includes, but is not limited to: peak hours, picking efficiency during peak hours, shelf efficiency, types of goods, quantity of goods, etc.
  • the networked supply chain decision-making platform establishes a warehouse capacity evaluation model in the warehouse. Based on the established warehousing capacity evaluation model, the input carrying capacity and output capacity of each link in the entire supply chain can be abstracted. At the same time, the optimal storage time and storage time of each link can be calculated, so that the entire supply All links of the chain are integrated and connected.
  • Step S20 Obtain the transaction record information corresponding to the seller, dynamically evaluate and predict the replenishment information corresponding to the seller based on the storage capacity evaluation model; at the same time, obtain the capacity information corresponding to the supplier.
  • the networked supply chain decision-making platform will analyze the transaction records corresponding to the seller according to the preset period, and combine the seller’s historical sales trends, etc., to predict the seller’s
  • the following sales situation within a preset time period; the sales situation of the seller includes: the sales forecast information of each store corresponding to the seller in different time periods in the future.
  • the specific duration of the above-mentioned preset period can be configured according to the specific region where the seller is located, the specific type of the goods it sells, etc., for example, if the sales goods have high requirements for timeliness, the network supply chain decision-making platform
  • the transaction records of the above-mentioned sellers can be analyzed in real time; if the sales commodity has low timeliness requirements, the specific duration of the preset period can be appropriately extended.
  • the seller's corresponding replenishment information such as the replenishment time and replenishment quantity required by the seller, can be dynamically evaluated and predicted.
  • the supplier will also publish its own capacity information or production plan information to the mesh supply chain decision-making platform; the mesh supply chain decision-making platform receives its own capacity information or production plan information released by the supplier .
  • Step S30 combining the transaction record information and replenishment information corresponding to the seller and the capacity information corresponding to the supplier, and intelligently matching the corresponding supplier and seller based on the corresponding warehousing capacity evaluation model.
  • the networked supply chain decision-making platform summarizes and integrates the transaction record information and replenishment information of the sellers and the capacity information of the supplier, and uses the established warehousing capacity evaluation model to intelligently match the supplier and the seller; for example, Recommend suppliers that meet the needs of sellers to corresponding sellers; at the same time, recommend matching sellers to suppliers, so that both sellers and suppliers can make two-way selection based on the intelligent matching results of the mesh supply chain decision-making platform.
  • the mesh supply chain decision-making platform matches the corresponding supplier for the seller, it will match based on the following factors: the current quotation of all suppliers on the mesh supply chain decision-making platform, the supplier’s credit rating, the seller’s historical sales, The seller’s future sales forecast and the processing capacity of the networked supply chain, etc.
  • the final decision of the networked supply chain decision-making platform is bidirectionally selected and determined by sellers and suppliers.
  • the networked supply chain sales platform in the daily operation of a certain seller A, will use the seller A’s inventory level, sales trend analysis information, and robot operation capability information and the network
  • the supply-demand relationship and other information on the sales platform of the supply chain are integrated and data analyzed, so as to determine the most suitable supplier for the seller A and the corresponding purchase quantity, procurement cycle, etc., and push the determined above information to the seller A, For the seller A to choose and confirm.
  • the networked supply chain decision-making platform can also push the above information to the supplier that is most suitable for the seller A, so that the corresponding supplier can also make a corresponding two-way selection of the seller A based on the pushed information.
  • the established warehousing capacity evaluation model described above will analyze and obtain all data based on the real-time data generated by the suppliers and sellers during the operation process with the continuous increase of operating data on the networked supply chain decision-making platform.
  • the real-time operating efficiency corresponding to the robot is described, and the warehousing capability evaluation model is revised and updated.
  • the networked supply chain decision-making platform automatically intelligently derives the corresponding supply and demand information based on the historical analysis results and the forecast result information for future predictions, and pushes the optimal production plan and procurement plan to the corresponding supply based on the obtained supply and demand information.
  • Suppliers and sellers so that suppliers and sellers can carry out production and sales planning based on the above-mentioned optimal production plan and purchase plan and other information pushed by the networked supply chain decision-making platform, thereby reducing freight costs and improving equipment utilization , And then achieve the purpose of reducing the inventory of both suppliers and sellers.
  • the networked supply chain decision-making platform will provide a series of models and strategy templates, so that both sellers and suppliers can more accurately describe their needs and capabilities based on the aforementioned models and strategy templates.
  • the networked supply chain decision-making platform will also analyze the data running on the platform in real time, so that the overall supply chain can realize real-time visualization and rapid response, making the entire networked supply chain decision-making platform more efficient.
  • clothing is taken as an example to describe the workflow of the networked supply chain decision-making platform; in this specific implementation, the networked supply chain decision-making platform is collectively referred to as a “platform”.
  • the clothing seller needs to register an account on the platform, choose its own business scope, and use the interface provided by the platform to connect with its own operating system such as ERP and POS systems.
  • the ERP system is an enterprise resource management system, which can effectively manage customers' purchase, sales and inventory, manage inventory and purchase orders, etc.
  • the POS system records all sales records of sellers.
  • the clothing seller interfaces with the platform the historical purchase records of the clothing seller are also imported into the platform.
  • the platform evaluates the purchase volume that the seller can bear, and uses the above-mentioned comprehensive data to evaluate the reasonable purchase quantity for the seller. At the same time, the platform evaluates the current inventory of the clothing suppliers registered on the platform. If there is a suitable inventory, the platform will notify the corresponding supplier and the seller of the appropriate purchase quantity and quotation at the same time. The two parties make two-way selection and final decision to determine whether to purchase.
  • the platform will release the seller’s needs based on the seller’s own information configuration and security configuration, and make specific production schedules; at the same time, according to the supplier
  • the production capacity of the company releases a reasonable production plan, so that the supplier can produce a batch of goods and the seller can digest a batch, thereby reducing the inventory of both parties to a minimum and improving the overall efficiency of the supply chain.
  • the robots running in the networked supply chain decision-making platform are managed by a robot management system. Based on the robot management system, obtain the operating information of the robots corresponding to the suppliers and sellers, and send the operating information of the robots to the networked supply chain decision-making platform for the decision-making platform to obtain based on the operating information
  • the operating efficiency of each robot wherein, the robot management system can run based on the decision platform and run in the decision platform, or can be independent of the decision platform and run separately; when the robot management system runs alone , The robot management system and the decision platform perform real-time information interaction.
  • the entire supply chain begins to circulate the order.
  • the robot can be used for handling.
  • the robot is used for handling and shelf loading. Robots can also be used for picking during subsequent sales.
  • the robot management system will also analyze the inbound and outbound data of the warehouse goods to further optimize the procurement cycle and quantity, and reduce the inventory pressure and capital occupation of sellers.
  • the robot management system analyzes the commodity warehousing data collected during operation of each robot, and according to the analysis result, provides an optimized solution containing purchase information for the seller for the seller’s reference ; At the same time, for suppliers to provide an optimized program containing capacity information for the supplier’s reference; wherein, the procurement information includes: commodity purchasing cycle, commodity purchasing category, and purchasing quantity corresponding to each purchasing category.
  • each level of the networked supply chain decision-making platform is operated by robots, and the operation information is collected through the robot management system, and the processing capabilities of each level of the supply chain are abstracted, and then combined with the networked supply chain For the supply and demand, the optimal purchase and production plans for sellers and suppliers are given respectively.
  • the networked supply chain decision-making platform analyzes the operating efficiency of the robots corresponding to the suppliers and the sellers respectively, and establishes a storage capacity evaluation model based on the operation of the robots, which can be implemented in the following manner:
  • the daily actual processing capacity information of each warehouse corresponding to each of the suppliers according to the daily actual processing capacity information of each warehouse, the basic capacity information of each level of storage corresponding to each of the suppliers and sellers is obtained;
  • the robot storage capacity information corresponding to each supply chain is obtained; wherein the storage capacity information includes order processing volume and corresponding orders Processing time;
  • the robot picking efficiency information corresponding to each store is obtained.
  • a simple supply chain system can be divided into five-level warehouses, supplier warehouses, transshipment centers, regional warehouses, front warehouses, and stores.
  • Each level of warehouses uses robots to perform operations. .
  • the actual processing capacity of each warehouse can be calculated every day. Including how many items can be processed every day and how many orders can be sorted every day. Abstract this as the basic ability of each level of storage.
  • Comprehensive evaluation of each line and the above nodes in the supply chain network can obtain the basic capabilities of each line, including processing orders and processing time.
  • the networked supply chain decision-making platform obtains the transaction record information corresponding to the seller, and dynamically evaluates and predicts the replenishment information corresponding to the seller based on the warehousing capacity evaluation model, which may be as follows Implementation:
  • the transaction record information corresponding to the seller combine the historical sales trend information of the seller, or combine the historical sales trend information and the corresponding environmental information, and predict that each store included in the seller will be preset in the future Sales forecast information within a period of time; according to the sales forecast information, based on the storage capacity evaluation model, dynamically evaluate and predict the replenishment information required by the seller; wherein, the replenishment information includes: corresponding to the seller Each store’s replenishment time, replenishment type, and replenishment quantity corresponding to different replenishment types.
  • the networked supply chain decision-making platform combines the transaction record information and replenishment information corresponding to the seller and the capacity information corresponding to the supplier, based on the corresponding storage capacity evaluation model , Smart matching of corresponding suppliers and sellers can be implemented as follows:
  • the transaction record information and replenishment information corresponding to the seller predict the possible sales volume within a preset time period in the future, and evaluate the sales according to the sales ability information of the seller in each sales link of the network supply chain
  • the purchase quantity information that the supplier may bear is synthesized to obtain the purchase information of the seller; at the same time, the current inventory information of the supplier is evaluated, and if the inventory information matches the purchase information of the seller, the purchase information
  • the purchasing information is pushed to matching suppliers, and the inventory information and corresponding quotation information are pushed to the matching sellers, so that the suppliers and sellers can make reference decisions and bidirectionally based on the pushed information, respectively. choose.
  • the networked supply chain decision-making platform will continuously analyze the merchant’s transaction records and combine historical sales trends to predict the seller’s sales in the next period of time. Situation, including sales forecasts for each store in different time periods in the future. According to the sales forecast, the time and quantity of replenishment are reversed.
  • suppliers will also publish their own production capacity or production plans on the networked supply chain decision-making platform.
  • the networked supply chain decision-making platform can also optimize the supplier’s production plan, recommending suppliers to produce on demand, and quickly Meet the needs of downstream.
  • the present invention is based on the robot-based network supply chain decision-making method, analyzes the operating efficiency of the respective robots corresponding to the suppliers and the sellers, establishes a storage capacity evaluation model based on the operation of the robots; obtains the transaction record information corresponding to the sellers, based on the storage
  • the capability evaluation model dynamically evaluates and predicts the replenishment information corresponding to the seller; at the same time, obtains the capacity information corresponding to the supplier; combines the transaction record information and replenishment information corresponding to the seller and the supplier corresponding
  • the production capacity information is intelligently matched to the corresponding suppliers and sellers; real-time visualization and rapid response of the entire supply chain are realized, and transportation costs, inventory costs, etc. in the supply chain process are reduced,
  • the use of robots greatly reduces personnel's daily planning and management work, and improves the user's service level in and out of the warehouse.
  • an embodiment of the present invention also provides a robot-based network supply chain decision-making device, as shown in FIG. 5, which is the robot-based method of the present invention.
  • FIG. 5 A schematic diagram of functional modules of an implementation of a networked supply chain decision-making device.
  • the embodiment of the present invention only describes the robot-based network supply chain decision-making device functionally, and the robot-based network supply chain decision-making device functionally includes: a model building module 100 and an intelligent matching module 200.
  • the model building module 100 is used to analyze the operation efficiency of the robots corresponding to the suppliers and the sellers respectively, and establish a storage capacity evaluation model based on the operation of the robots.
  • the intelligent matching module 200 is used to obtain transaction record information corresponding to the seller, dynamically evaluate and predict the replenishment information corresponding to the seller based on the storage capacity evaluation model; at the same time, obtain the capacity information corresponding to the supplier.
  • the present invention is based on the robot-based network supply chain decision-making device, analyzes the operating efficiency of the robots corresponding to the suppliers and the sellers, and establishes a storage capacity evaluation model based on the operation of the robots; obtains the transaction record information corresponding to the sellers, based on the storage
  • the capability evaluation model dynamically evaluates and predicts the replenishment information corresponding to the seller; at the same time, obtains the capacity information corresponding to the supplier; combines the transaction record information and replenishment information corresponding to the seller and the supplier corresponding
  • the production capacity information is intelligently matched to the corresponding suppliers and sellers; real-time visualization and rapid response of the entire supply chain are realized, and transportation costs, inventory costs, etc. in the supply chain process are reduced,
  • the use of robots greatly reduces personnel's daily planning and management work, and improves the user's service level in and out of the warehouse.
  • FIG. 6 is a schematic diagram of the internal structure of an embodiment of the electronic device of the present invention.
  • the electronic device 1 may be a PC (Personal Computer, personal computer), or a terminal device such as a smart phone, a tablet computer, or a portable computer.
  • the electronic device 1 at least includes a memory 11, a processor 12, a communication bus 13, and a network interface 14.
  • the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), magnetic memory, magnetic disk, optical disk, and the like.
  • the memory 11 may be an internal storage unit of the electronic device 1 in some embodiments, such as a hard disk of the electronic device 1.
  • the memory 11 may also be an external storage device of the electronic device 1, such as a plug-in hard disk equipped on the electronic device 1, a smart memory card (Smart Media Card, SMC), Secure Digital (Secure Digital, SD) card, flash card (Flash Card), etc.
  • the memory 11 may also include both an internal storage unit of the electronic device 1 and an external storage device.
  • the memory 11 can be used not only to store application software and various data installed in the electronic device 1, such as the code of the network supply chain decision program 01, etc., but also to temporarily store data that has been output or will be output.
  • the processor 12 may be a central processing unit (Central Processing Unit) in some embodiments.
  • Central Processing Unit Central Processing Unit
  • CPU Central Processing Unit
  • controller microcontroller
  • microprocessor microprocessor or other data processing chip, used to run the program code or processing data stored in the memory 11, for example, execute the network supply chain decision-making program 01 and so on.
  • the communication bus 13 is used to realize the connection and communication between these components.
  • the network interface 14 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface), and is usually used to establish a communication connection between the electronic device 1 and other electronic devices.
  • a standard wired interface and a wireless interface such as a WI-FI interface
  • the electronic device 1 may further include a user interface.
  • the user interface may include a display (Display) and an input unit such as a keyboard (Keyboard).
  • the optional user interface may also include a standard wired interface and a wireless interface.
  • the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch device, etc.
  • the display can also be appropriately called a display screen or a display unit, which is used to display the information processed in the electronic device 1 and to display a visualized user interface.
  • Figure 6 only shows the electronic device 1 with components 11-14 and the networked supply chain decision-making program 01. Those skilled in the art can understand that the structure shown in Figure 6 does not constitute a limitation on the electronic device 1. Including fewer or more components than shown, or combining some components, or different component arrangements.
  • the network supply chain decision program 01 is stored in the memory 11; the network supply chain decision program 01 stored on the memory 11 can be stored in When running on the processor 12, the network supply chain decision-making program 01 is executed by the processor 12 to implement the following steps:
  • the embodiment of the present invention also provides a computer storage medium, the computer storage medium stores a network supply chain decision program, and the network supply chain decision program can be executed by one or more processors to realize Next operation:
  • the specific implementation of the computer-readable storage medium of the present invention is basically the same as the implementation principles of the foregoing robot-based network supply chain decision-making methods, devices, and electronic equipment corresponding to the implementation principles, and will not be repeated here.
  • the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware.
  • the present invention is a cross-platform evaluation table analysis method, equipment and storage medium, analyzes the operating efficiency of the robots corresponding to the suppliers and the sellers respectively, establishes a storage capacity evaluation model based on the operation of the robots; obtains the corresponding information of the sellers Transaction record information, based on the storage capacity evaluation model, dynamically evaluate and predict the replenishment information corresponding to the seller; at the same time, obtain the capacity information corresponding to the supplier; combine the transaction record information and replenishment information corresponding to the seller As well as the capacity information corresponding to the supplier, based on the corresponding warehousing capacity evaluation model, the corresponding supplier and seller are intelligently matched; real-time visualization and rapid response of the entire supply chain are realized, and transportation in the supply chain is reduced. Costs, inventory costs, etc., and the use of robot operations also greatly reduces personnel's daily planning and management work, and improves the user's warehousing service level. Therefore, it has industrial applicability.

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Abstract

一种基于机器人的网状供应链决策方法、设备及存储介质，该方法包括：分析供应商和销售商各自分别对应的机器人的运作效率，建立基于机器人运行的仓储能力评估模型(S10)；获取所述销售商对应的交易记录信息，基于仓储能力评估模型，动态评估和预测所述销售商对应的补货信息；同时，获取供应商对应的产能信息(S20)；结合所述销售商对应的所述交易记录信息和补货信息以及所述供应商对应的所述产能信息，基于对应的仓储能力评估模型，智能匹配对应的供应商和销售商(S30)；实现了整个供应链的实时可视化和快速响应，降低了供应链过程中的运输成本和库存成本，同时减少了人员的日常计划和管理工作，提升了用户的出入库服务水平。

Description

基于机器人的网状供应链决策方法、设备及存储介质 技术领域
本发明涉及物流技术领域，特别涉及一种基于机器人的网状供应链决策方法、设备及存储介质。
 背景技术
传统供应链通常指的是：制造、采购、存储、发货、配送的整个管理链条。在这个传统的供应链条中，信息流、物流、资金流沿着这个供应链条进行不断地流动。由于在上述传统供应链对应的每一个环节中，都会有大量的中间商等，与此同时，供应链人员也需要同时处理不同的信息来源。例如，对于一名采购人员而言，上游会有制造商，也会有各种供应商，采购人员需要对接多个渠道，每天需要同时处理大量的信息；而由于部分信息获取途径存在滞后性、不准确性等问题，因此获取的上述信息可能存在不准确、不及时的问题，而采购人员基于获取的上述不准确、不及时的信息所做出的决策，可能会大大降低供应链的整体效率，增加交易成本。
另外，目前也有很多供应链企业引入了机器人来进行仓储拣货和搬运等业务，但是目前机器人只是单纯的进行执行动作，机器人在运作当中产生的大量执行数据并没有得到利用，也无法去反哺上游的业务操作；因此，造成了上下游环节的脱节。上游依然需要依靠大量的人力和传统经验进行决策，而下游的机器人产生的数据也没有被利用起来。综上，目前传统供应链的消息传递低效且供需匹配需要人工重度参与，效率低。
 技术问题
本发明提供一种基于机器人的网状供应链决策方法、设备及存储介质，旨在提供一种在网状供应链中进行智能供需匹配的技术方案。
 技术解决方案
第一方面，本发明提供了一种基于机器人的网状供应链决策方法，包括：
分析供应商和销售商各自分别对应的机器人的运作效率，建立基于机器人运行的仓储能力评估模型；获取所述销售商对应的交易记录信息，基于仓储能力评估模型，动态评估和预测所述销售商对应的补货信息；同时，获取供应商对应的产能信息；结合所述销售商对应的所述交易记录信息和补货信息以及所述供应商对应的所述产能信息，基于对应的仓储能力评估模型，智能匹配对应的供应商和销售商。
第二方面，本发明提供了一种基于机器人的网状供应链决策平台，包括模型建立模块和智能匹配模块。
其中：所述模型建立模块用于：分析供应商和销售商各自分别对应的机器人的运作效率，建立基于机器人运行的仓储能力评估模型。
所述智能匹配模块用于：获取所述销售商对应的交易记录信息，基于仓储能力评估模型，动态评估和预测所述销售商对应的补货信息；同时，获取供应商对应的产能信息；结合所述销售商对应的所述交易记录信息和补货信息以及所述供应商对应的所述产能信息，基于对应的仓储能力评估模型，智能匹配对应的供应商和销售商。
第三方面，本发明提供了一种电子设备，所述电子设备包括存储器和处理器，所述存储器上存储有可在所述处理器上运行的基于机器人的网状供应链决策程序，所述网状供应链决策程序被所述处理器运行时，执行所述的基于机器人的网状供应链决策方法。
第四方面，本发明提供了一种计算机存储介质，所述存储介质上存储有基于机器人的网状供应链决策程序，所述网状供应链决策程序可以被一个或者多个处理器执行，以实现所述的基于机器人的网状供应链决策方法的步骤。
 有益效果
本发明一种跨平台的估值表解析方法、设备及存储介质，分析供应商和销售商各自分别对应的机器人的运作效率，建立基于机器人运行的仓储能力评估模型；获取所述销售商对应的交易记录信息，基于仓储能力评估模型，动态评估和预测所述销售商对应的补货信息；同时，获取供应商对应的产能信息；结合所述销售商对应的所述交易记录信息和补货信息以及所述供应商对应的所述产能信息，基于对应的仓储能力评估模型，智能匹配对应的供应商和销售商；实现了整个供应链的实时可视化和快速响应，降低了供应链过程中的运输成本、库存成本等，同时利用机器人作业也极大地减少了人员的日常计划和管理工作，提升了用户的出入库服务水平。
 附图说明
附图用来提供对本发明的进一步理解，并且构成说明书的一部分，与本发明的实施例一起用于解释本发明，并不构成对本发明的限制。在附图中：
图1是本发明基于机器人的网状供应链决策方法中网状供应链的一种实施方式的示意图。
图2是传统供应链模式示意图。
图3是本发明基于机器人的网状供应链决策方法的一种实施方式的流程示意图。
图4是本发明基于机器人的网状供应链决策方法中多级供应链的一种实施方式的示意图。
图5是本发明基于机器人的网状供应链决策装置的一种实施方式的功能模块示意图。
图6是本发明电子设备的一种实施方式的内部结构示意图。
 本发明的实施方式
以下结合附图对本发明的优选实施例进行说明，应当理解，此处所描述的优选实施例仅用于说明和解释本发明，并不用于限定本发明。
本发明提供了一种基于机器人的网状供应链决策方法、设备及存储介质，该方案提供了一种网状供应链决策平台，为供应链的各个环节提供了一个数据沟通、共享和决策参考的平台。如图1所示，图1是本发明基于机器人的网状供应链决策方法中网状供应链的一种实施方式的示意图。基于图1所示的网状供应链平台，比如，销售商可以在该网状供应链平台上发布需求，比如描述自身的需求品类、需求数量以及其他需求信息等。同时，供应商也会在该网状供应链决策平台上发布自己的生产能力、定价等一系列的产能信息，该网状供应链决策平台会根据销售商的历史销量和当季销售数据对供货源进行比较，同时根据销售商的对应情况创建对应的仓储能力评估模型进行评估，直接给销售商提供包含最优的货源价格和数量等信息的供应商信息，销售商即可根据该网状供应链决策平台提供的上述供应商信息，进行选择并做出最终的决策。同时，该网状供应链决策平台也会给供应商提供相应的生产建议，并将该网状供应链中的生产需求信息快速传递。
相比于传统链式供应链，网状供应链将所有的供应商和销售商比如采购者结合在一张关系网当中，将所有的供需信息通过网络进行传递。同时通过建立仓储能力评估模型进行计算，且能够结合大数据预测，平衡供需，将各方的利益最大化。通过网状供应链决策平台，销售商的采购者可以获取到更优的采购周期、采购数量和采购价格，同时供应商也会得到更优的生产数量和生产周期，供需双方都从网状供应链中得到了成本的优化。如此以来，相较于图2所示的传统供应链模式，本发明提供的基于机器人的网状供应链可以降低供应链的交易成本，提升供应链的运行效率，同时减少因信息迟滞和信息不准确所造成的损失。
另外，本发明提供的基于机器人的网状供应链决策方法、设备及存储介质中，融入了机器人运行时的相关数据，充分利用了机器人运行过程当中所产生的大量执行数据，进而根据机器人运行时产生的执行数据去反哺该网状供应链决策平台中的上游业务操作，从而使得该网状供应链的上下游的数据融合贯通，在决策时融入了机器人的运行数据，也使得决策方案的制定更加智能和客观。
如图3所示，图3是本发明基于机器人的网状供应链决策方法的一种实施方式的流程示意图，所述基于机器人的网状供应链决策方法包括步骤S10-S30。
步骤S10、分析供应商和销售商各自分别对应的机器人的运作效率，建立基于机器人运行的仓储能力评估模型。
本发明实施例中，供应商和销售商基于机器人进行货物的运输、分拣、上货等操作。网状供应链决策平台分析供应商和销售商对应的机器人的运作效率，包括但不限于：机器人的拣货效率、上架效率、机器人日常运作的高峰信息和低峰信息等相关信息；其中，高峰信息包括但不限于：高峰时段、高峰时段内的拣货效率、上架效率以及货物种类、货物数量等。根据对上述数据的分析结果，网状供应链决策平台建立仓库内的仓储能力评估模型。基于建立的仓储能力评估模型，即可抽象出整个供应链中每一个环节的输入承载能力和输出能力，同时也可以计算出每个环节的最佳入库时间和出库时间，从而将整个供应链的各个环节融合贯通。
步骤S20、获取所述销售商对应的交易记录信息，基于仓储能力评估模型，动态评估和预测所述销售商对应的补货信息；同时，获取供应商对应的产能信息。
在该网状供应链决策平台的正常运行过程中，该网状供应链决策平台会按照预设周期分析销售商对应的交易记录，同时结合该销售商的历史销售趋势等，预测该销售商在接下来的预设时长内的销售情况；该销售商的销售情况包括：该销售商对应的每个门店在未来不同时段内的销售预测信息。其中，上述预设周期的具体时长可以根据该销售商所在的具体地域、其销售商品所属的具体种类等进行配置，比如若该销售商品对时效性要求较高，则该网状供应链决策平台可以对上述销售商的交易记录进行实时分析；若该销售商品对时效性要求较低，则可以适当延长该预设周期的具体时长。基于仓储能力评估模型，根据上述销售预测信息，即可动态评估和预测该销售商对应的补货信息，比如该销售商所需的补货时间和补货数量等。同时，在供应商侧，供应商也会将自身的产能信息或者生产计划信息发布到该网状供应链决策平台上；该网状供应链决策平台接收供应商发布的自身产能信息或者生产计划信息。
步骤S30、结合所述销售商对应的所述交易记录信息和补货信息以及所述供应商对应的所述产能信息，基于对应的仓储能力评估模型，智能匹配对应的供应商和销售商。
该网状供应链决策平台对销售商的交易记录信息和补货信息以及供应商的产能信息进行汇总和整合，利用建立的上述仓储能力评估模型，将供应商和销售商进行智能匹配；比如，将满足销售商需求的供应商推荐给对应的销售商；同时，将匹配的销售商也推荐给供应商，以便销售商和供应商双方基于网状供应链决策平台的智能匹配结果进行双向选择。网状供应链决策平台将为销售商匹配对应的供应商时，基于如下要素进行匹配：当前网状供应链决策平台上所有供应商的报价、供应商的信用等级、该销售商的历史销量、该销售商的未来销售预测以及该网状供应链的处理能力等。另外，该网状供应链决策平台的最终决策由销售商和供应商双向选择和确定。
比如，基于网状供应链决策平台，某销售商A在日常的运行过程中，该网状供应链销售平台将该销售商A的库存水平、销售趋势分析信息、以及机器人运行能力信息和该网状供应链销售平台上供需关系等信息进行整合和数据分析，从而确定最适合该销售商A的供应商以及对应的采购数量、采购周期等，并将确定的上述信息推送至该销售商A，供该销售商A进行选择和确定。同时，该网状供应链决策平台也可以将上述信息推送至最适合该销售商A对应的供应商，以便对应的供应商基于推送的上述信息同时也对销售商A进行相应的双向选择。
本发明实施例中，建立的上述仓储能力评估模型随着该网状供应链决策平台上运行数据的不断增加，根据所述供应商和销售商在运行过程中产生的实时数据，分析并获取所述机器人对应的实时运作效率，修正并更新该仓储能力评估模型。
该网状供应链决策平台自动根据历史分析结果以及对未来预测的预测结果信息智能得出对应的供需信息，根据得出的供需信息，将最优的生产计划和采购计划等推送至相应的供应商和销售商，从而使得供应商和销售商能够基于该网状供应链决策平台推送的上述最优生产计划和采购计划等信息，进行生产和销售规划等，从而减少货运成本，提升设备利用率，进而达到降低供应商和销售商双方库存的目的。
在一个实施例中，该网状供应链决策平台会提供一系列的模型和策略模板等，以便销售商和供应商双方基于上述模型和策略模板等更加精确地描述自身的需求和能力。同时，该网状供应链决策平台也会实时对该平台上运行的数据进行分析，从而整体的供应链实现实时地可视化和快速响应，使得整个网状供应链决策平台的运行更加高效。
比如，在一个具体的应用场景中，以服装为例来描述该网状供应链决策平台的工作流程；在该具体实施方式中，将网状供应链决策平台统称为“平台”。在具体的应用中，该服装销售商需要在该平台上注册一个账号，选择自己的经营范围，同时需要使用平台提供的接口与自己所使用的操作系统比如ERP、POS系统等进行对接。其中，ERP系统是企业资源管理系统，可以有效的管理客户的进销存，管理库存和采购订单等；POS系统记录了销售商所有的销售记录。在该服装销售商与该平台进行对接接口的同时，将该服装销售商的历史采购记录一并导入到该平台中。同时，也有相应的服装供应商加入到平台当中，将自己生产的产品类型、型号等信息上传到平台中。另外，服装供应商将自身可生产的商品上传到平台时，为了便于数据处理，需要该服装供应商按照统一的格式进行数据上传，比如一种商品在平台中的流转采用统一商品码等。销售商各级供应链仓库中使用机器人进行作业，平台对机器人分拣和上架的效率进行统计，结合每一级仓库中的机器人数量，计算出每一级的处理能力。例如转运中心每天可以处理10万件入库，15万件出库。前置仓每天可以处理3000单的出库订单。平台会根据销售商的销售情况进行动态评估和预测。例如去年同时期某衬衫销量较好，则根据去年同期的销量来预测未来的销售量。平台根据供应链各环节的能力评估出该销售商能够承受的进货量，并利用上述综合数据进行评估得出针对该销售商的合理的采购数量。同时，平台对该平台上已注册的服装供应商的当前库存进行评估，如果有合适的库存量，则该平台会将合适的采购数量和报价同时通知给对应的供应商和该销售商，由双方进行双向选择和最终决策，从而确定是否进行采购。如果目前平台上并没有合适的相匹配的服装库存量，则该平台基于销售商自身的信息配置和安全配置，将销售商的需求进行发布，且进行具体的生产排期；同时，根据供应商的生产能力发布合理的生产计划，使得供应商生产出一批商品、销售商就能消化一批，从而将双方的库存都降到最低，提升了供应链的整体效率。
在一个实施例中，该网状供应链决策平台中运行的机器人由机器人管理系统进行管理。基于机器人管理系统，获取所述供应商和销售商分别对应的机器人的运行信息，并将所述机器人的运行信息发送至网状供应链决策平台，供所述决策平台基于所述运行信息，得到各机器人的运作效率；其中，所述机器人管理系统可基于所述决策平台运行并运行在所述决策平台内，也可以独立于所述决策平台并单独运行；当所述机器人管理系统单独运行时，所述机器人管理系统与所述决策平台进行实时信息交互。
比如，基于网状供应链决策平台的智能匹配，销售商在网状供应链决策平台下单后，整个供应链开始进行订单的流转，在流转的过程中，结合所述机器人管理系统中的机器人解决方案。订单下发给相匹配的供应商后，可以使用机器人进行搬运。货物送到销售商对应的仓库中后，使用机器人进行搬运、上架等工作。后续销售过程中也可以使用机器人进行拣货。同时在上架、拣货过程中，机器人管理系统也会对仓库商品的出入库数据进行分析，进一步去优化采购周期和数量，减轻销售商的库存压力和资金占用。
进一步地，在一个实施例中，所述机器人管理系统对各机器人运行时采集的商品出入库数据进行分析，并根据分析结果，针对销售商提供包含采购信息的优化方案，供所述销售商参考；同时，针对供应商提供包含产能信息的优化方案，供所述供应商参考；其中，所述采购信息包括：商品采购周期、商品采购种类以及各采购种类分别对应的采购数量。本发明实施例中，网状供应链决策平台中每一级都是采用机器人运作的，并通过机器人管理系统采集运行信息、抽象出每一级供应链的处理能力，然后再结合网状供应链的供需，分别给出销售商和供应商最优的采购、生产计划等。
进一步地，在一个实施例中，网状供应链决策平台分析供应商和销售商各自分别对应的机器人的运作效率，建立基于机器人运行的仓储能力评估模型，可以按照如下方式实施：
针对供应商和销售商，分别获取各自运行的机器人数量和所述机器人在预设历史时长内对应的历史作业效率；根据获取的所述机器人数量和历史作业效率，计算获取所述供应商和销售商各自分别对应的每一个仓库每天的实际处理能力信息；根据所述每一个仓库每天的实际处理能力信息，得到所述供应商和销售商各自分别对应的每一级仓储的基本能力信息；在供应商侧，根据网状供应链网络中包含的每一条供应链以及对应的仓储节点，得到每一条供应链分别对应的机器人仓储能力信息；其中，所述仓储能力信息包括订单处理量和对应订单的处理时长；在销售商侧，根据所述销售商对应的不同的门店信息，得到每一个门店分别对应的机器人拣货效率信息。
比如，在图4所述的实施例中，简单的供应链体系可以分为五级仓库，供应商仓库、转运中心、区域仓库、前置仓、门店，每一级仓库都使用机器人进行做作业。根据仓库当中的机器人数量和历史作业效率，可以算出每一个仓库每天的实际处理能力。包括每天能处理多少件商品入库，每天可以分拣多少张订单。将这个抽象为每一级仓储的基本能力。将供应链网络中每一条线和上面的节点综合评估，就可以得到每一条线的基本能力，包括处理单量和处理时间等。
进一步地，在一个实施例中，网状供应链决策平台获取所述销售商对应的交易记录信息，基于仓储能力评估模型，动态评估和预测所述销售商对应的补货信息，可以按照如下方式实施：
获取所述销售商对应的交易记录信息，结合所述销售商的历史销售趋势信息，或者结合所述历史销售趋势信息和对应的环境信息，预测所述销售商包含的每个门店在未来预设时长内的销售预测信息；根据所述销售预测信息，基于仓储能力评估模型，动态评估和预测所述销售商所需的补货信息；其中，所述补货信息包括：所述销售商对应的每个门店的补货时间、补货种类以及不同的补货种类分别对应的补货数量。
进一步地，在一个实施例中，网状供应链决策平台结合所述销售商对应的所述交易记录信息和补货信息以及所述供应商对应的所述产能信息，基于对应的仓储能力评估模型，智能匹配对应的供应商和销售商，可以按照如下方式实施：
根据销售商对应的所述交易记录信息和补货信息，预测在未来预设时长内可能的销售量，并根据所述销售商在网状供应链各销售环节的销售能力信息，评估所述销售商可能承受的进货量信息，综合得出所述销售商的采购信息；同时，评估所述供应商当前的库存信息，若所述库存信息与所述销售商的采购信息相匹配，则将所述采购信息推送至相匹配的供应商，以及将所述库存信息和对应的报价信息推送至相匹配的所述销售商，供所述供应商和销售商分别基于推送的信息进行参考决策和双向选择。
比如，在一个具体的应用场景中，销售商在正常运行过程中，网状供应链决策平台会不断分析商户的交易记录，同时结合历史销售趋势等，预测销售商在接下来一段时间内的销售情况，包括每个门店在未来不同时段内的销售预测。根据销售预测反推出需要补货的时间和数量。与此同时供应商也会将自己的产能或者生产计划发布到网状供应链决策平台上，该网状供应链决策平台也可以对供应商的生产计划进行优化，推荐供应商按需生产，快速满足下游的需求。
本发明基于机器人的网状供应链决策方法，分析供应商和销售商各自分别对应的机器人的运作效率，建立基于机器人运行的仓储能力评估模型；获取所述销售商对应的交易记录信息，基于仓储能力评估模型，动态评估和预测所述销售商对应的补货信息；同时，获取供应商对应的产能信息；结合所述销售商对应的所述交易记录信息和补货信息以及所述供应商对应的所述产能信息，基于对应的仓储能力评估模型，智能匹配对应的供应商和销售商；实现了整个供应链的实时可视化和快速响应，降低了供应链过程中的运输成本、库存成本等，同时利用机器人作业也极大地减少了人员的日常计划和管理工作，提升了用户的出入库服务水平。
对应于上述实施例描述的基于机器人的网状供应链决策方法，本发明实施例还提供了一种基于机器人的网状供应链决策装置，如图5所示，图5是本发明基于机器人的网状供应链决策装置的一种实施方式的功能模块示意图。本发明实施例仅仅从功能上来描述基于机器人的网状供应链决策装置，该基于机器人的网状供应链决策装置在功能上包括：模型建立模块100和智能匹配模块200。
其中，所述模型建立模块100用于：分析供应商和销售商各自分别对应的机器人的运作效率，建立基于机器人运行的仓储能力评估模型。
所述智能匹配模块200用于：获取所述销售商对应的交易记录信息，基于仓储能力评估模型，动态评估和预测所述销售商对应的补货信息；同时，获取供应商对应的产能信息。
结合所述销售商对应的所述交易记录信息和补货信息以及所述供应商对应的所述产能信息，基于对应的仓储能力评估模型，智能匹配对应的供应商和销售商。
本发明实施例的具体实施方式与上述基于机器人的网状供应链决策方法的各实施例的实施原理基本相同，在此不作累述。
本发明基于机器人的网状供应链决策装置，分析供应商和销售商各自分别对应的机器人的运作效率，建立基于机器人运行的仓储能力评估模型；获取所述销售商对应的交易记录信息，基于仓储能力评估模型，动态评估和预测所述销售商对应的补货信息；同时，获取供应商对应的产能信息；结合所述销售商对应的所述交易记录信息和补货信息以及所述供应商对应的所述产能信息，基于对应的仓储能力评估模型，智能匹配对应的供应商和销售商；实现了整个供应链的实时可视化和快速响应，降低了供应链过程中的运输成本、库存成本等，同时利用机器人作业也极大地减少了人员的日常计划和管理工作，提升了用户的出入库服务水平。
本发明还提供了一种电子设备，所述电子设备可以按照图3所述的基于机器人的网状供应链决策方法进行供需双方的智能匹配。如图6所示，图6是本发明电子设备的一种实施方式的内部结构示意图。
在本实施例中，电子设备1可以是PC（Personal Computer，个人电脑），也可以是智能手机、平板电脑、便携计算机等终端设备。该电子设备1至少包括存储器11、处理器12，通信总线13，以及网络接口14。
其中，存储器11至少包括一种类型的可读存储介质，所述可读存储介质包括闪存、硬盘、多媒体卡、卡型存储器（例如，SD或DX存储器等）、磁性存储器、磁盘、光盘等。存储器11在一些实施例中可以是电子设备1的内部存储单元，例如该电子设备1的硬盘。存储器11在另一些实施例中也可以是电子设备1的外部存储设备，例如电子设备1上配备的插接式硬盘，智能存储卡（Smart Media Card, SMC），安全数字（Secure Digital, SD）卡，闪存卡（Flash Card）等。进一步地，存储器11还可以既包括电子设备1的内部存储单元也包括外部存储设备。存储器11不仅可以用于存储安装于电子设备1的应用软件及各类数据，例如网状供应链决策程序01的代码等，还可以用于暂时地存储已经输出或者将要输出的数据。
处理器12在一些实施例中可以是一中央处理器（Central Processing Unit, CPU）、控制器、微控制器、微处理器或其他数据处理芯片，用于运行存储器11中存储的程序代码或处理数据，例如执行网状供应链决策程序01等。
通信总线13用于实现这些组件之间的连接通信。
网络接口14可选的可以包括标准的有线接口、无线接口（如WI-FI接口），通常用于在该电子设备1与其他电子设备之间建立通信连接。
可选地，该电子设备1还可以包括用户接口，用户接口可以包括显示器（Display）、输入单元比如键盘（Keyboard），可选的用户接口还可以包括标准的有线接口、无线接口。可选地，在一些实施例中，显示器可以是LED显示器、液晶显示器、触控式液晶显示器以及OLED（Organic Light-Emitting Diode，有机发光二极管）触摸器等。其中，显示器也可以适当的称为显示屏或显示单元，用于显示在电子设备1中处理的信息以及用于显示可视化的用户界面。
图6仅示出了具有组件11-14以及网状供应链决策程序01的电子设备1，本领域技术人员可以理解的是，图6示出的结构并不构成对电子设备1的限定，可以包括比图示更少或者更多的部件，或者组合某些部件，或者不同的部件布置。
基于上述实施例的描述，在图6所示的电子设备1的实施例中，存储器11中存储有网状供应链决策程序01；所述存储器11上存储的网状供应链决策程序01可在所述处理器12上运行，所述网状供应链决策程序01被所述处理器12运行时实现如下步骤：
分析供应商和销售商各自分别对应的机器人的运作效率，建立基于机器人运行的仓储能力评估模型；获取所述销售商对应的交易记录信息，基于仓储能力评估模型，动态评估和预测所述销售商对应的补货信息；同时，获取供应商对应的产能信息；结合所述销售商对应的所述交易记录信息和补货信息以及所述供应商对应的所述产能信息，基于对应的仓储能力评估模型，智能匹配对应的供应商和销售商。
本发明实施例的具体实施方式与上述基于机器人的网状供应链决策方法及装置的各实施例的实施原理基本相同，在此不作累述。
此外，本发明实施例还提供了一种计算机存储介质，所述计算机存储介质上存储有网状供应链决策程序，所述网状供应链决策程序可以被一个或者多个处理器执行，以实现下操作：
分析供应商和销售商各自分别对应的机器人的运作效率，建立基于机器人运行的仓储能力评估模型；
获取所述销售商对应的交易记录信息，基于仓储能力评估模型，动态评估和预测所述销售商对应的补货信息；同时，获取供应商对应的产能信息；
结合所述销售商对应的所述交易记录信息和补货信息以及所述供应商对应的所述产能信息，基于对应的仓储能力评估模型，智能匹配对应的供应商和销售商。
本发明计算机可读存储介质具体实施方式与上述基于机器人的网状供应链决策方法、装置和电子设备对应的各实施例的实施原理基本相同，在此不作累述。
本领域内的技术人员应明白，本发明的实施例可提供为方法、系统、或计算机程序产品。因此，本发明可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。
显然，本领域的技术人员可以对本发明进行各种改动和变型而不脱离本发明的精神和范围。这样，倘若本发明的这些修改和变型属于本发明权利要求及其等同技术的范围之内，则本发明也意图包含这些改动和变型在内。
 工业实用性
本发明一种跨平台的估值表解析方法、设备及存储介质，分析供应商和销售商各自分别对应的机器人的运作效率，建立基于机器人运行的仓储能力评估模型；获取所述销售商对应的交易记录信息，基于仓储能力评估模型，动态评估和预测所述销售商对应的补货信息；同时，获取供应商对应的产能信息；结合所述销售商对应的所述交易记录信息和补货信息以及所述供应商对应的所述产能信息，基于对应的仓储能力评估模型，智能匹配对应的供应商和销售商；实现了整个供应链的实时可视化和快速响应，降低了供应链过程中的运输成本、库存成本等，同时利用机器人作业也极大地减少了人员的日常计划和管理工作，提升了用户的出入库服务水平。因此，具有工业实用性。

Claims (10)

  1. 一种基于机器人的网状供应链决策方法，所述网状供应链决策方法包括：
    分析供应商和销售商各自分别对应的机器人的运作效率，建立基于机器人运行的仓储能力评估模型；
    获取所述销售商对应的交易记录信息，基于仓储能力评估模型，动态评估和预测所述销售商对应的补货信息；同时，获取供应商对应的产能信息；
    结合所述销售商对应的所述交易记录信息和补货信息以及所述供应商对应的所述产能信息，基于对应的仓储能力评估模型，智能匹配对应的供应商和销售商。
  2. 如权利要求1所述的基于机器人的网状供应链决策方法，其中，所述网状供应链决策方法还包括：
    基于机器人管理系统，获取所述供应商和销售商分别对应的机器人的运行信息，并将所述机器人的运行信息发送至网状供应链决策平台，供所述决策平台基于所述运行信息，得到各机器人的运作效率；
    其中，所述机器人管理系统可基于所述决策平台运行并运行在所述决策平台内，也可以独立于所述决策平台并单独运行；当所述机器人管理系统单独运行时，所述机器人管理系统与所述决策平台进行实时信息交互。
  3. 如权利要求2所述的基于机器人的网状供应链决策方法，其中，所述网状供应链决策方法还包括：
    所述机器人管理系统对各机器人运行时采集的商品出入库数据进行分析，并根据分析结果，针对销售商提供包含采购信息的优化方案，供所述销售商参考；同时，针对供应商提供包含产能信息的优化方案，供所述供应商参考；其中，所述采购信息包括：商品采购周期、商品采购种类以及各采购种类分别对应的采购数量。
  4. 如权利要求1所述的基于机器人的网状供应链决策方法，其中，所述网状供应链决策方法还包括：
    根据所述供应商和销售商在运行过程中产生的实时数据，分析并获取所述机器人对应的实时运作效率，修正并更新所述仓储能力评估模型。
  5. 如权利要求1至4任一项所述的基于机器人的网状供应链决策方法，其中，所述分析供应商和销售商各自分别对应的机器人的运作效率，建立基于机器人运行的仓储能力评估模型，包括：
    针对供应商和销售商，分别获取各自运行的机器人数量和所述机器人在预设历史时长内对应的历史作业效率；
    根据获取的所述机器人数量和历史作业效率，计算获取所述供应商和销售商各自分别对应的每一个仓库每天的实际处理能力信息；
    根据所述每一个仓库每天的实际处理能力信息，得到所述供应商和销售商各自分别对应的每一级仓储的基本能力信息；
    在供应商侧，根据网状供应链网络中包含的每一条供应链以及对应的仓储节点，得到每一条供应链分别对应的机器人仓储能力信息；其中，所述仓储能力信息包括订单处理量和对应订单的处理时长；
    在销售商侧，根据所述销售商对应的不同的门店信息，得到每一个门店分别对应的机器人拣货效率信息。
  6. 如权利要求1至4任一项所述的基于机器人的网状供应链决策方法，其中，所述获取所述销售商对应的交易记录信息，基于仓储能力评估模型，动态评估和预测所述销售商对应的补货信息，包括：
    获取所述销售商对应的交易记录信息，结合所述销售商的历史销售趋势信息，或者结合所述历史销售趋势信息和对应的环境信息，预测所述销售商包含的每个门店在未来预设时长内的销售预测信息；
    根据所述销售预测信息，基于仓储能力评估模型，动态评估和预测所述销售商所需的补货信息；其中，所述补货信息包括：所述销售商对应的每个门店的补货时间、补货种类以及不同的补货种类分别对应的补货数量。
  7. 如权利要求1至4任一项所述的基于机器人的网状供应链决策方法，其中，所述结合所述销售商对应的所述交易记录信息和补货信息以及所述供应商对应的所述产能信息，基于对应的仓储能力评估模型，智能匹配对应的供应商和销售商，包括：
    根据销售商对应的所述交易记录信息和补货信息，预测在未来预设时长内可能的销售量，并根据所述销售商在网状供应链各销售环节的销售能力信息，评估所述销售商可能承受的进货量信息，综合得出所述销售商的采购信息；
    同时，评估所述供应商当前的库存信息，若所述库存信息与所述销售商的采购信息相匹配，则将所述采购信息推送至相匹配的供应商，以及将所述库存信息和对应的报价信息推送至相匹配的所述销售商，供所述供应商和销售商分别基于推送的信息进行参考决策和双向选择。
  8. 一种基于机器人的网状供应链决策平台，其中，所述网状供应链决策平台包括模型建立模块和智能匹配模块；其中：
    所述模型建立模块用于：分析供应商和销售商各自分别对应的机器人的运作效率，建立基于机器人运行的仓储能力评估模型；
    所述智能匹配模块用于：
    获取所述销售商对应的交易记录信息，基于仓储能力评估模型，动态评估和预测所述销售商对应的补货信息；同时，获取供应商对应的产能信息；
    结合所述销售商对应的所述交易记录信息和补货信息以及所述供应商对应的所述产能信息，基于对应的仓储能力评估模型，智能匹配对应的供应商和销售商。
  9. 一种电子设备，所述电子设备包括存储器和处理器，所述存储器上存储有可在所述处理器上运行的基于机器人的网状供应链决策程序，所述网状供应链决策程序被所述处理器运行时，执行如权利要求1至7中任一项所述的基于机器人的网状供应链决策方法。
  10. 一种计算机存储介质，所述存储介质上存储有基于机器人的网状供应链决策程序，所述网状供应链决策程序可以被一个或者多个处理器执行，以实现如权利要求1至7中任一项所述的基于机器人的网状供应链决策方法的步骤。
PCT/CN2021/084526 2020-04-30 2021-03-31 基于机器人的网状供应链决策方法、设备及存储介质 WO2021218553A1 (zh)

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