WO2023082549A1 - 多因素约束下面向多式联运的制造任务分配方法及装置 - Google Patents

多因素约束下面向多式联运的制造任务分配方法及装置 Download PDF

Info

Publication number
WO2023082549A1
WO2023082549A1 PCT/CN2022/088226 CN2022088226W WO2023082549A1 WO 2023082549 A1 WO2023082549 A1 WO 2023082549A1 CN 2022088226 W CN2022088226 W CN 2022088226W WO 2023082549 A1 WO2023082549 A1 WO 2023082549A1
Authority
WO
WIPO (PCT)
Prior art keywords
cost
time
task
total
economic cost
Prior art date
Application number
PCT/CN2022/088226
Other languages
English (en)
French (fr)
Inventor
刘旭
林浩生
罗贺
陈彦宇
吴萍
郭强
Original Assignee
珠海格力电器股份有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 珠海格力电器股份有限公司 filed Critical 珠海格力电器股份有限公司
Publication of WO2023082549A1 publication Critical patent/WO2023082549A1/zh

Links

Images

Classifications

    • 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
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06313—Resource planning in a project environment
    • 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
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06315—Needs-based resource requirements planning or analysis
    • 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
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Definitions

  • the present disclosure relates to the technical field of resource allocation, and in particular to a method and device for multimodal transport-oriented manufacturing task allocation under the constraints of multiple factors.
  • Some domestic manufacturing enterprises need to purchase domestic semi-finished products (also known as spare parts) for processing when building factories overseas. After domestic sales demand overseas is converted into domestic purchase orders, raw materials are purchased and processed, and through ports and shipping The company transports all orders to foreign countries through the logistics network, and finally completes the receipt of payment through a specific settlement center to achieve a closed-loop business. This process includes procurement, production and processing, warehousing, transshipment, financial settlement and other links. Selecting appropriate manufacturing service resources for different manufacturing tasks is a resource allocation problem.
  • the allocation of resources is mainly done by manual calculation in the market. Although it can be optimized to a certain extent, from the perspective of the manufacturing environment, the problem of resource allocation for manufacturing tasks has the heterogeneity of manufacturing service resources and the complexity of manufacturing service resource networks. It is difficult to consider the optimization of resource allocation from the perspective of overall planning, so there are problems such as low efficiency in resource allocation and unreasonable allocation of service resources.
  • the present disclosure provides a multimodal transport-oriented manufacturing task allocation method and device under the constraints of multiple factors, which solves the difficulty of considering the optimization of resource allocation from an overall perspective, so there are problems in task allocation. Unreasonable allocation of service resources and other issues.
  • An embodiment of the present disclosure provides a method for allocating manufacturing tasks to multimodal transport under multi-factor constraints, including: obtaining order requirements, decomposing the order requirements into multiple task requirements; obtaining the completion of each task based on the task requirements The time cost and economic cost of all tasks; the total time cost and total economic cost of completing the order are obtained based on the time cost and the economic cost of all tasks; the time cost and the economic cost of each task, the order The total time cost and the total economic cost are optimized for resource allocation.
  • the task requirements include: at least one of procurement tasks, production and processing tasks, warehousing tasks, transshipment tasks, and settlement tasks.
  • the time cost includes: at least one of procurement time, production time, storage time, transshipment time, and financial service time.
  • the economic cost includes: at least one of procurement cost, production cost, storage cost, transshipment cost, and financial service cost.
  • the step of obtaining the total time cost and total economic cost of completing an order based on the time cost and the economic cost of all tasks includes: based on the time cost and the economic cost of all tasks, in The total time cost and total economic cost of completing the order are obtained under the constraints of the collaborative relationship.
  • the synergy relationship includes: at least one of a regional synergy relationship and a time synergy relationship.
  • the step of optimizing the time cost and the economic cost of each task, the total time cost and the total economic cost of an order comprises: using a genetics algorithm to optimize each The time cost and the economic cost of the task, the total time cost and the total economic cost of the order are optimized.
  • a manufacturing task allocation device for multimodal transportation under multi-factor constraints including: an acquisition module, used to acquire order requirements, and decompose the order requirements into multiple task requirements; a calculation module, used to obtain The time cost and the economic cost of completing each task; the total time cost and the total economic cost of completing the order are obtained based on the time cost and the economic cost of all tasks; the optimization module is used for the time cost of each task and the economic cost, the total time cost of the order and the total economic cost are optimized for resource allocation.
  • An electronic device including a memory and a processor, the memory is used to store one or more computer instructions, wherein, when the one or more computer instructions are executed by the processor, any one of the above-mentioned embodiments can be implemented Multimodal transport-oriented manufacturing task assignment method under the multi-factor constraints mentioned above.
  • a computer-readable storage medium where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, it is used to implement the multi-factor-oriented multimodal Intermodal manufacturing task assignment method.
  • the embodiment of the present disclosure provides a multi-factor constraint-oriented manufacturing task allocation method and device for multimodal transportation. From the perspective of system engineering, the service resources involved in the entire supply chain are considered, and these services and their corresponding tasks are performed.
  • the combination optimization of one-to-one matching achieves the purpose of comprehensive overall planning and optimization of resource allocation, reduces the phenomenon of resource idleness or resource shortage, enables service resources to be allocated reasonably, and improves the efficiency of the overall process of manufacturing resource allocation.
  • FIG. 1 is a flowchart of a multimodal transportation-oriented manufacturing task allocation method under multi-factor constraints provided by an embodiment of the present disclosure.
  • FIG. 2 is a schematic diagram of a multimodal transportation-oriented manufacturing task allocation method provided by an embodiment of the present disclosure under multi-factor constraints.
  • FIG. 3 is a schematic structural diagram of a multimodal transport-oriented manufacturing task allocation device provided by an embodiment of the present disclosure under multi-factor constraints.
  • This embodiment provides a method for allocating manufacturing tasks to multimodal transport under multi-factor constraints.
  • the method for allocating manufacturing tasks to multi-modal transport under multi-factor constraints includes:
  • Step 01 Obtain order requirements, and decompose the order requirements into multiple task requirements.
  • the task requirements include: procurement tasks, production and processing tasks, warehousing tasks, transshipment tasks and settlement tasks.
  • Step 02 Obtain the time cost and economic cost of completing each task based on the task requirements.
  • the time consumed by the service of the large ship or small ship is the port time of the large ship or small ship, which is composed of the sum of the difference between the actual departure time of the large ship or small ship at the port and the start time of operation, and the cost incurred by the large ship or small ship service is the large ship or small ship service
  • the total cost is composed of the sum of the product of the position price and the number of positions of each large ship or small ship; financial services mainly consider two types of costs, one is the transaction cost of the selected financial institution, and the impact of the exchange rate factor on the final cost at the time of settlement .
  • the time cost includes: at least one of procurement time, production time, storage time, transit time, and financial service time.
  • the economic cost includes: at least one of procurement cost, production cost, storage cost, transshipment cost, and financial service cost.
  • Formula (1) is the purchase time, Indicates the procurement start time of the k ij supplier, Indicates the purchase arrival time of the k ij supplier, is a decision variable, 1 means to choose the k ij supplier, and 0 means not to choose;
  • formula (2) is the procurement cost, Indicates the unit material procurement cost of the k ij supplier, Indicates the material purchase quantity of the k ij supplier.
  • Formula (3) is the production time, Indicates the waiting time required for production at the k ijth production base, Indicates the service time required for the k ij production base, is a decision variable, if it is 1, it means to choose the k ij production base, if it is 0, it means not to choose;
  • the formula (4) is the production cost, Indicates the unit production cost of the k ij production base, Indicates the production quantity of the k ijth production base.
  • Formula (5) is the storage time
  • T SM (k ij ) represents the storage time of the material at the k ij warehouse
  • T SP (k ij ) represents the storage time of the finished product at the k ij warehouse
  • formula (6) is the material storage time, Indicates the production start time of the k ij production base, Indicates the purchase arrival time of the k ij supplier
  • formula (7) is the finished product storage time, Indicates the time when the big ship starts working in the port, Indicates the production end time of the k ij production base
  • formula (8) indicates the storage cost, Indicates the required storage space for the k ijth warehouse of the material, Indicates the storage space required by the finished product at the k ij warehouse, Indicates the storage cost of the k ijth warehouse unit material or finished product, is a decision variable, 1 means to choose the k ij warehouse, and 0 means not to choose.
  • Formula (9) is the time of the big ship in port, Indicates the actual departure time of the big ship at the port, Indicates the time when the big ship starts working in the port, is a decision variable, 1 means to choose the large ship service in the k ij time period, and 0 means not to choose;
  • formula (10) is the cost of large ship service, C VT (k ij ) represents the transportation cost from warehouse or inland river port to large ship port , C VB (k ij ) represents the booking cost of a large ship;
  • formula (11) represents the transportation cost from a warehouse or an inland river port to a large ship port, c VT represents the unit distance transportation cost from a warehouse or an inland river port to a large ship port, and d is a constant, expressing The Euclidean distance between the warehouse and the port;
  • formula (12) represents the booking cost of a large ship, Indicates the big ship position price in the k ij time period, Indicates the number of large ship positions in
  • Formula (13) is the boat's time in port, Indicates the actual departure time of the boat at the port, Indicates the time when the boat starts working in port, is a decision variable, 1 means to choose the small boat service in the k ij time period, and 0 means not to choose;
  • the formula (14) is the small boat service cost, C BT (k ij ) means the transportation cost from the warehouse to the inland port, C BB (k ij ) represents the booking cost of small boats;
  • formula (15) represents the transportation cost from the warehouse to the inland port, c BT represents the transportation cost per unit distance from the warehouse to the inland port, and d is a constant, representing the Euclidean distance between the warehouse and the port ;
  • Equation (16) represents the booking cost of a small boat, Indicates the position price of the boat in the k ij time period, Indicates the number of boat positions in the k ij time period.
  • Formula (17) is the financial service time
  • T FI (k ij ) represents the service time of the financial institution
  • 1 means to choose the kij -th financial institution
  • 0 means not to choose
  • Formula (18) is the financial service cost
  • C FI (k ij ) means the service cost of the financial institution.
  • Step 03 Obtain the total time cost and total economic cost of completing the order based on the time cost and the economic cost of all tasks.
  • formula (19) is the objective function, T represents the total time, C represents the total cost, ⁇ 1 and ⁇ 2 represent the weights of time and cost respectively;
  • formula (20) is the total time function, T P , T M , T S , T V , T B , and TF respectively represent the purchase time, production time, storage time, large ship transportation time, small ship transportation time, and financial service time;
  • formula (21) is the total cost function, and C P , C M , C S , C V , C B , and CF represent purchase cost, production cost, warehousing cost, large ship transportation cost, small ship transportation cost, and financial service cost, respectively.
  • Step 04 optimize the time cost and the economic cost of each task, the total time cost and the total economic cost of the order, so that the objective function in formula 19 obtains the time and cost weighted sum minimum Perform optimal resource allocation.
  • a genetic algorithm is used to optimize the time cost and the economic cost of each task, the total time cost and the total economic cost of an order, so as to obtain an optimal resource allocation method.
  • Genetic algorithm is a method of random global search and optimization of the solution of the problem by simulating the biological evolution mechanism in nature. Each chromosome in the genetic algorithm corresponds to a solution. The adaptability of the solution is evaluated through the fitness function to judge the pros and cons of the solution. Genetic algorithm is the process of seeking the optimal solution through continuous search and optimization.
  • the total time cost and the total economic cost of completing an order are obtained under the constraints of the collaborative relationship.
  • the collaborative relationship can be expressed as:
  • Formula (22) is a time constraint, which means that the actual completion time of the manufacturing task cannot exceed the latest completion time; formula (23) is a cost constraint, which means that the total cost cannot exceed the estimated maximum cost; formula (24) is a regional coordination constraint, which means The production base and the warehouse belong to the same place; formula (25) means that the meaningless time in the two processes from the arrival of purchased materials to the start of production, and from the end of production to transportation to Brazil is less than a constraint value; formula (26) means that each A manufacturing task can only be completed by a manufacturing service.
  • the synergy relationship includes: at least one of a regional synergy relationship and a time synergy relationship.
  • the production capacity service and the storage capacity service need to be selected in the same region.
  • the storage time of materials and finished products in the warehouse has a great impact on the inventory cost. Reducing the residence time of raw materials and finished products in the warehouse can greatly save costs. This means that the time of purchasing materials, production time and transportation time needs to maintain a large degree of coordination.
  • the time difference between the purchase arrival time and the start of production time, the end of production and the start of transportation time is meaningless. Time, the smaller the meaningless time, the smaller the cost of occupying the warehouse.
  • This embodiment provides a multimodal transportation-oriented manufacturing task allocation device 100 under multi-factor constraints. As shown in FIG. 20 and optimization module 30.
  • the obtaining module 10 is used to obtain order requirements, and decompose the order requirements into multiple task requirements;
  • the calculation module 20 is used to obtain the time cost and the economic cost of completing each task based on the task requirements; obtain the total time cost and the total economic cost of completing the order based on the time cost and the economic cost of all tasks;
  • the optimization module 30 is configured to optimize the time cost and the economic cost of each task, the total time cost and the total economic cost of an order, so as to perform resource allocation.
  • the acquisition module 10 decomposes the order requirement into multiple task requirements.
  • the task requirements include: at least one of procurement tasks, production and processing tasks, warehousing tasks, transshipment tasks and settlement tasks;
  • calculation module 20 obtains the time cost and the economic cost of completing each task based on the task requirements, and obtains the total time cost and the total economic cost of completing the order based on the time cost and the economic cost of all tasks; afterward, optimize Module 30 optimizes the time cost and the economic cost of each task, the total time cost and the total economic cost of the order to perform resource allocation, and optionally, utilizes a genetics algorithm for each task The time cost and the economic cost of the order, the total time cost and the total economic cost of the order are optimized.
  • the calculation module 20 obtains the total time cost and the total economic cost of completing the order based on the time cost and the economic cost of all tasks under the constraints of the synergy relationship.
  • the synergy relationship includes: At least one of a regional synergy relationship and a time synergy relationship.
  • This embodiment provides an electronic device.
  • This embodiment provides an electronic device.
  • the electronic device includes a memory and a processor, and a computer program is stored in the memory. When the computer program is executed by the processor, the above embodiments are implemented.
  • electronic devices can also include, input/output (I/O) interfaces, and communication components.
  • the processor is configured to execute all or part of the steps in the multimodal transport-oriented manufacturing task allocation method under multi-factor constraints as in the embodiment.
  • the memory is used to store various types of data, which may include, for example, instructions of any application or method in the electronic device, as well as application-related data.
  • the processor can be an application specific integrated circuit (Application Specific Integrated Circuit, referred to as ASIC), a digital signal processor (Digital Signal Processor, referred to as DSP), a programmable logic device (Programmable Logic Device, referred to as PLD), field programmable gate array (Field Programmable Gate Array, referred to as FPGA), controller, microcontroller, microprocessor or other electronic components, used to implement the multimodal transportation-oriented manufacturing task allocation method under the multi-factor constraints in the above embodiments.
  • ASIC Application Specific Integrated Circuit
  • DSP Digital Signal Processor
  • PLD programmable logic device
  • FPGA field programmable gate array
  • controller microcontroller
  • microprocessor or other electronic components used to implement the multimodal transportation-oriented manufacturing task allocation method under the multi-factor constraints in the above embodiments.
  • Described memory can be realized by any type of volatile or non-volatile memory device or their combination, such as Static Random Access Memory (Static Random Access Memory, referred to as SRAM), Electrically Erasable Programmable Read-Only Memory (EPROM) Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), Erasable Programmable Read-Only Memory (Erasable Programmable Read-Only Memory, referred to as EPROM), Programmable Read-Only Memory (Programmable Read-Only Memory, referred to as PROM), read-only Memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, magnetic disk or optical disk.
  • SRAM Static Random Access Memory
  • EPROM Electrically Erasable Programmable Read-Only Memory
  • EEPROM Electrically Erasable Programmable Read-Only Memory
  • EPROM Erasable Programmable Read-Only Memory
  • PROM Programmable Read-Only Memory
  • ROM Read-Only Memory
  • magnetic memory flash
  • This embodiment also provides a computer-readable storage medium.
  • Each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit. If the functions described above are realized in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium.
  • the technical solution of the present disclosure is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in various embodiments of the present disclosure.
  • a computer device which may be a personal computer, a server, or a network device, etc.
  • the aforementioned storage medium includes: flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), computer Erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, server, APP application store and other media that can store program verification codes, on which are stored
  • flash memory hard disk
  • multimedia card for example, SD or DX memory, etc.
  • card-type memory for example, SD or DX memory, etc.
  • RAM random access memory
  • SRAM static random access memory
  • ROM read-only memory
  • EEPROM computer Erasable programmable read-only memory
  • PROM programmable read-only memory
  • magnetic memory magnetic disk, optical disk, server, APP application store and other media that can store program verification codes, on which are stored
  • APP application store and other media that can store program verification codes, on which are stored
  • Step 01 Obtain order requirements, and decompose the order requirements into multiple task requirements
  • Step 02 obtain the time cost and economic cost of completing each task based on the task requirement
  • Step 03 obtain the total time cost and the total economic cost of completing the order based on the time cost and the economic cost of all tasks;
  • Step 04 Optimizing the time cost and the economic cost of each task, the total time cost and the total economic cost of an order, so as to allocate resources.
  • the disclosed systems, devices and methods may be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the units is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components can be combined or May be integrated into another system, or some features may be ignored, or not implemented.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
  • each component or each step can be decomposed and/or reassembled. These decompositions and/or recombinations should be considered equivalents of the present disclosure.
  • plural means at least two, such as two, three, etc., unless otherwise specifically defined. All directional indications (such as up, down, left, right, front, back, top, bottom%) in the embodiments of the present disclosure are only used to explain the relationship between the various components in a certain posture (as shown in the drawings) If the specific posture changes, the directional indication will also change accordingly. Furthermore, the terms “comprising” and “having”, as well as any variations thereof, are intended to cover a non-exclusive inclusion.
  • a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but optionally also includes unlisted steps or units, or optionally further includes For other steps or units inherent in these processes, methods, products or apparatuses.
  • an embodiment means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present disclosure.
  • the occurrences of this phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is understood explicitly and implicitly by those skilled in the art that the embodiments described herein can be combined with other embodiments.

Landscapes

  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Engineering & Computer Science (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • Tourism & Hospitality (AREA)
  • Marketing (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Educational Administration (AREA)
  • Game Theory and Decision Science (AREA)
  • Development Economics (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Manufacturing & Machinery (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

一种多因素约束下面向多式联运的制造任务分配方法及装置，解决了难以从统筹全局的角度考虑资源配置的最优化，因此在任务分配上存在效率低、服务资源分配不合理等问题。所述多因素约束下面向多式联运的制造任务分配方法包括：获取订单需求，将所述订单需求分解成多个任务需求；基于所述任务需求得到完成每个任务的时间成本和经济成本；基于所有任务的所述时间成本和所述经济成本得到完成订单的总时间成本和总经济成本；对每个任务的所述时间成本和所述经济成本、订单的所述总时间成本和所述总经济成本进行优化，以进行资源配置。

Description

多因素约束下面向多式联运的制造任务分配方法及装置
交叉引用
本公开引用于2021年11月12日提交的专利名称为“多因素约束下面向多 式联运的制造任务分配方法及装置”的第202111346102.5号中国专利申请，其 通过引用被全部并入本公开。
技术领域
本公开涉及资源配置技术领域，具体涉及一种多因素约束下面向多式联运的制造任务分配方法及装置。
背景技术
有些国内制造企业在海外建厂需要采购国内的半成品(也可称散件)进行加工，国内对接海外的销售需求后转换成国内的采购订单，采购原材料并进行生产加工，并通过港口和船务公司将所有订单通过物流网络运输到国外，最后再通过特定的结算中心完成货款接收，实现业务闭环。这一过程中包括采购、生产加工、仓储、转运、金融结算等环节，为不同环节的制造任务选择合适的制造服务资源属于资源配置问题。
目前市场上主要通过人工计算来完成资源的配置，虽然可以在一定程度上进行优化，但是从制造业大环境来看，制造任务资源配置问题具有制造服务资源异构性、制造服务资源网络复杂化等特征，仅依赖于人工经验，难以从统筹全局的角度考虑资源配置的最优化，因此存在资源配置上存在效率低、服务资源分配不合理等问题。
发明内容
有鉴于此，本公开提供了一种多因素约束下面向多式联运的制造任务分配方法及装置，解决了难以从统筹全局的角度考虑资源配置的最优化，因此在任务分配上存在效率低、服务资源分配不合理等问题。
本公开一实施例提供的一种多因素约束下面向多式联运的制造任务分配方 法包括：获取订单需求，将所述订单需求分解成多个任务需求；基于所述任务需求得到完成每个任务的时间成本和经济成本；基于所有任务的所述时间成本和所述经济成本得到完成订单的总时间成本和总经济成本；对每个任务的所述时间成本和所述经济成本、订单的所述总时间成本和所述总经济成本进行优化，以进行资源配置。
在一种实施方式中，所述任务需求包括：采购任务、生产加工任务、仓储任务、转运任务和结算任务中的至少一种。
在一种实施方式中，所述时间成本包括：采购时间、生产时间、仓储时间、转运时间、金融服务时间中的至少一种。
在一种实施方式中，所述经济成本包括：采购成本、生产成本、仓储成本、转运成本、金融服务成本中的至少一种。
在一种实施方式中，基于所有任务的所述时间成本和所述经济成本得到完成订单的总时间成本和总经济成本的步骤包括：基于所有任务的所述时间成本和所述经济成本，在协同关系的约束下得到完成订单的总时间成本和总经济成本。
在一种实施方式中，所述协同关系包括：地域协同关系和时间协同关系中的至少一种。
在一种实施方式中，所述对每个任务的所述时间成本和所述经济成本、订单的所述总时间成本和所述总经济成本进行优化的步骤包括：利用遗传学算法对每个任务的所述时间成本和所述经济成本、订单的所述总时间成本和所述总经济成本进行优化。
一种多因素约束下面向多式联运的制造任务分配装置，包括：获取模块，用于获取订单需求，将所述订单需求分解成多个任务需求；计算模块，用于基于所述任务需求得到完成每个任务的时间成本和经济成本；基于所有任务的所述时间成本和所述经济成本得到完成订单的总时间成本和总经济成本；优化模块，用于对每个任务的所述时间成本和所述经济成本、订单的所述总时间成本和所述总经济成本进行优化，以进行资源配置。
一种电子设备，包括存储器和处理器，所述存储器用于存储一条或多条计算机指令，其中，所述一条或多条计算机指令被所述处理器执行时实现上述实施例中任意一项所述的多因素约束下面向多式联运的制造任务分配方法。
一种计算机可读存储介质，所述计算机可读存储介质中存储有计算机程序， 所述计算机程序被处理器执行时用以实现上述实施例中任意一项所述的多因素约束下面向多式联运的制造任务分配方法。
本公开实施例提供的一种多因素约束下面向多式联运的制造任务分配方法及装置，从系统工程的角度，考虑了整个供应链上涉及到的服务资源，对这些服务与其对应的任务进行一对一匹配的组合优化，达到了综合统筹优化资源配置的目的，降低了资源闲置或资源紧缺的现象，使得服务资源得到了合理的分配，提高了制造资源配置整体流程的效率。
附图说明
图1所示为本公开一实施例提供的一种多因素约束下面向多式联运的制造任务分配方法的流程图。
图2所示为本公开一实施例提供的一种多因素约束下面向多式联运的制造任务分配方法的示意图。
图3所示为本公开一实施例提供的一种多因素约束下面向多式联运的制造任务分配装置的结构示意图。
具体实施方式
下面将结合本公开实施例中的附图，对本公开实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅是本公开一部分实施例，而不是全部的实施例。基于本公开中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本公开保护的范围。
本实施例提供一种多因素约束下面向多式联运的制造任务分配的方法，如图1和图2所示所述多因素约束下面向多式联运的制造任务分配的方法包括：
步骤01:获取订单需求，将所述订单需求分解成多个任务需求。
可选地，将订单按照采购、生产加工、仓储、转运和结算服务五个环节进行任务分解得到任务需求，所述任务需求包括：采购任务、生产加工任务、仓储任务、转运任务和结算任务。
步骤02:基于所述任务需求得到完成每个任务的时间成本和经济成本。
分别由采购、生产加工、仓储、转运和结算服务五个环节中涉及到的供应商服务、生产服务、仓储服务和大船或小船服务等所耗费的总时间和产生的总成本 构成，可选地，大船或小船服务消耗的时间为大船或小船在港时间，由大船或小船在港口的实际离港时间和开始作业时间的差值之和构成，大船或小船服务产生的成本为大船或小船服务总成本，由大船或小船各自的仓位价格和仓位数量的乘积之和构成；金融服务主要考虑两类成本，一是选择的金融机构的交易成本，而是结算时汇率的因素对最终成本的影响。
可选地，时间成本包括：采购时间、生产时间、仓储时间、转运时间、金融服务时间中的至少一种。
可选地，经济成本包括：采购成本、生产成本、仓储成本、转运成本、金融服务成本中的至少一种。
下面将分别对上述时间成本和经济成本的计算过程进行说明：
(1)采购任务：
Figure PCTCN2022088226-appb-000001
Figure PCTCN2022088226-appb-000002
公式(1)为采购时间，
Figure PCTCN2022088226-appb-000003
表示在第k ij家供应商的采购开始时间，
Figure PCTCN2022088226-appb-000004
表示第k ij家供应商采购到货时间，
Figure PCTCN2022088226-appb-000005
为决策变量，为1表示选择第k ij家供应商，为0则表示不选择；公式(2)为采购成本，
Figure PCTCN2022088226-appb-000006
表示第k ij家供应商单位物料采购成本，
Figure PCTCN2022088226-appb-000007
表示在第k ij家供应商的物料采购数量。
(2)生产加工任务：
Figure PCTCN2022088226-appb-000008
Figure PCTCN2022088226-appb-000009
公式(3)为生产时间，
Figure PCTCN2022088226-appb-000010
表示在第k ij个生产基地生产所需的等待时间，
Figure PCTCN2022088226-appb-000011
表示第k ij个生产基地生产所需的服务时间，
Figure PCTCN2022088226-appb-000012
为决策变量，为1表示选择第k ij个生产基地，为0则表示不选择；公式(4)为生产成本，
Figure PCTCN2022088226-appb-000013
表示第k ij个生产基地的单位生产成本，
Figure PCTCN2022088226-appb-000014
表示在第k ij个生产基地的生产数量。
(3)仓储任务：
Figure PCTCN2022088226-appb-000015
Figure PCTCN2022088226-appb-000016
Figure PCTCN2022088226-appb-000017
Figure PCTCN2022088226-appb-000018
公式(5)为仓储时间，T SM(k ij)表示物料在第k ij个仓库的仓储时间，T SP(k ij)表示成品在第k ij个仓库的仓储时间；公式(6)为物料仓储时间，
Figure PCTCN2022088226-appb-000019
表示在第k ij家生产基地的生产开始时间，
Figure PCTCN2022088226-appb-000020
表示第k ij家供应商采购到货时间；公式(7)为成品仓储时间，
Figure PCTCN2022088226-appb-000021
表示大船在港口开始作业的时间，
Figure PCTCN2022088226-appb-000022
表示在第k ij家生产基地的生产结束时间；公式(8)表示仓储成本，
Figure PCTCN2022088226-appb-000023
表示物料第k ij个仓库的需要的仓储空间，
Figure PCTCN2022088226-appb-000024
表示成品在第k ij个仓库的需要的仓储空间，
Figure PCTCN2022088226-appb-000025
表示第k ij个仓库单位物料或成品的仓储成本，
Figure PCTCN2022088226-appb-000026
为决策变量，为1表示选择第k ij个仓库，为0则表示不选择。
(4)转运任务：
大船服务：
Figure PCTCN2022088226-appb-000027
Figure PCTCN2022088226-appb-000028
Figure PCTCN2022088226-appb-000029
Figure PCTCN2022088226-appb-000030
公式(9)为大船在港时间，
Figure PCTCN2022088226-appb-000031
表示大船在港口的实际离港时间，
Figure PCTCN2022088226-appb-000032
表示大船在港口开始作业的时间，
Figure PCTCN2022088226-appb-000033
为决策变量，为1表示选择第k ij时间段的大船服务，为0则表示不选择；公式(10)为大船服务成本，C VT(k ij)表示仓库或内河港到大船港的运输成本，C VB(k ij)表示大船订舱成本；公式(11)为仓库或内河港到大船港的运输成本，c VT表示仓库或内河港到大船港的单位距离运输成 本，d为常数，表示仓库与港口之间的欧氏距离；公式(12)表示大船订舱成本，
Figure PCTCN2022088226-appb-000034
表示第k ij时间段的大船仓位价格，
Figure PCTCN2022088226-appb-000035
表示在第k ij时间段的大船仓位数量。
小船服务：
Figure PCTCN2022088226-appb-000036
Figure PCTCN2022088226-appb-000037
Figure PCTCN2022088226-appb-000038
Figure PCTCN2022088226-appb-000039
公式(13)为小船在港时间，
Figure PCTCN2022088226-appb-000040
表示小船在港口的实际离港时间，
Figure PCTCN2022088226-appb-000041
表示小船在港口开始作业的时间，
Figure PCTCN2022088226-appb-000042
为决策变量，为1表示选择第k ij时间段的小船服务，为0则表示不选择；公式(14)为小船服务成本，C BT(k ij)表示仓库到内河港的运输成本，C BB(k ij)表示小船订舱成本；公式(15)为仓库到内河港的运输成本，c BT表示仓库到内河港的单位距离运输成本，d为常数，表示仓库与港口之间的欧氏距离；公式(16)表示小船订舱成本，
Figure PCTCN2022088226-appb-000043
表示第k ij时间段的小船仓位价格，
Figure PCTCN2022088226-appb-000044
表示在第k ij时间段的小船仓位数量。
(5)金融任务：
Figure PCTCN2022088226-appb-000045
Figure PCTCN2022088226-appb-000046
公式(17)为金融服务时间，T FI(k ij)表示金融机构的服务时间，
Figure PCTCN2022088226-appb-000047
为决策变量，为1表示选择第k ij家的金融机构，为0则表示不选择；公式(18)为金融服务成本，C FI(k ij)表示金融机构的服务成本。
步骤03:基于所有任务的所述时间成本和所述经济成本得到完成订单的总时间成本和总经济成本。
其中，基于所有任务的所述时间成本和所述经济成本得到完成订单的总时间成本和总经济成本的公式为：
minF＝ω 1T+ω 2C                     (19)
T＝T P+T M+T S+T V+T B+T F                 (20)
C＝C P+C M+C S+C V+C B+C F                 (21)
其中，公式(19)为目标函数，T表示总时间，C表示总成本，ω 1和ω 2分别表示时间和成本所占的权重；公式(20)为总时间函数，T P、T M、T S、T V、T B、T F分别表示采购时间、生产时间、仓储时间、大船运输时间、小船运输时间、金融服务时间；公式(21)为总成本函数，C P、C M、C S、C V、C B、C F分别表示采购成本、生产成本、仓储成本、大船运输成本、小船运输成本、金融服务成本。
步骤04:对每个任务的所述时间成本和所述经济成本、订单的所述总时间成本和所述总经济成本进行优化，使公式19中的目标函数得到时间和成本加权和最小值以进行最优资源配置。
可选地，利用遗传学算法对每个任务的所述时间成本和所述经济成本、订单的所述总时间成本和所述总经济成本进行优化，以得到最优的资源配置方法。遗传算法是一种模拟自然界生物进化机制对问题的解进行随机全局搜索和优化的方法。遗传算法中的每一条染色体对应一个解决方案。通过适应度函数对解决方案进行适应性评价，以此来判别方案的优劣。遗传算法是通过不断的搜索和优化寻求最优解的过程。
在本公开一实施例中，基于所有任务的所述时间成本和所述经济成本，在协同关系的约束下得到完成订单的总时间成本和总经济成本。
协同关系可用公式表示为：
T≤T max                         (22)
C≤C max                         (23)
RS＝0                          (24)
TS≤g                          (25)
Figure PCTCN2022088226-appb-000048
公式(22)为时间约束，指制造任务的实际完成时间不能超过最晚完成时间；公式(23)为成本约束，指总成本不能超过估计的最大成本；公式(24)为地域协同约束，指生产基地和仓库属于同一个地方；公式(25)为从采购物料到货到开始生产、从生产结束到运输至巴西这两个过程中的无意义时间小于一个约束值；公式(26)为每个制造任务只能由一个制造服务完成。
可选地，所述协同关系包括：地域协同关系和时间协同关系中的至少一种。
基于协同关系量化的地域协同关系与时间协同关系的计算公式为：
(1)地域协同
Figure PCTCN2022088226-appb-000049
Figure PCTCN2022088226-appb-000050
生产能力服务与仓储能力服务需要选择在同一地域。
(2)时间协同
TS＝t u
Figure PCTCN2022088226-appb-000051
物料和成品在仓库的存储时间对库存成本有很大影响，减少原料和成品在仓库中的滞留时间，可以很大程度节约成本。这就意味着，采购物料时间、生产时间和运输时间三者需要保持很大的协同度，采购到货时间与开始生产时间、生产结束与开始运输时间，两两之间时间差值为无意义时间，无意义时间越小，则表明占用仓库的成本越小。
本实施例提供一种多因素约束下面向多式联运的制造任务分配装置100，如图3所示，所述多因素约束下面向多式联运的制造任务分配装置100包括获取模块10、计算模块20和优化模块30。
获取模块10用于获取订单需求，将所述订单需求分解成多个任务需求；
计算模块20用于基于所述任务需求得到完成每个任务的时间成本和经济成本；基于所有任务的所述时间成本和所述经济成本得到完成订单的总时间成本和总经济成本；
优化模块30用于对每个任务的所述时间成本和所述经济成本、订单的所述总时间成本和所述总经济成本进行优化，以进行资源配置。
获取模块10获取到订单需求后，将所述订单需求分解成多个任务需求，可选地，任务需求包括：采购任务、生产加工任务、仓储任务、转运任务和结算任务中的至少一种；然后计算模块20基于所述任务需求得到完成每个任务的时间成本和经济成本，以及基于所有任务的所述时间成本和所述经济成本得到完成订单的总时间成本和总经济成本；之后，优化模块30对每个任务的所述时间成本 和所述经济成本、订单的所述总时间成本和所述总经济成本进行优化，以进行资源配置，可选地，利用遗传学算法对每个任务的所述时间成本和所述经济成本、订单的所述总时间成本和所述总经济成本进行优化。
除此之外，计算模块20基于所有任务的所述时间成本和所述经济成本，在协同关系的约束下得到完成订单的总时间成本和总经济成本，可选地，所述协同关系包括：地域协同关系和时间协同关系中的至少一种。
本实施例中得到所有任务的所述时间成本和所述经济成本、完成订单的总时间成本和总经济成本以及协同关系的计算等等同上述实施例中所述，在此不再赘述。
本实施例提供一种电子设备，本实施例提供了一种电子设备，该电子设备包括存储器和处理器，所述存储器上存储有计算机程序，该计算机程序被处理器执行时实现如上述实施例中所述的多因素约束下面向多式联运的制造任务分配方法可以理解，电子设备还可以包括，输入/输出(I/O)接口，以及通信组件。
其中，处理器用于执行如实施例中的多因素约束下面向多式联运的制造任务分配方法中的全部或部分步骤。存储器用于存储各种类型的数据，这些数据例如可以包括电子设备中的任何应用程序或方法的指令，以及应用程序相关的数据。
所述处理器可以是专用集成电路(Application Specific Integrated Cricuit，简称ASIC)、数字信号处理器(Digital Signal Processor，简称DSP)、可编程逻辑器件(Programmable Logic Device，简称PLD)、现场可编程门阵列(Field Programmable Gate Array，简称FPGA)、控制器、微控制器、微处理器或其他电子元件实现，用于执行上述实施例中的多因素约束下面向多式联运的制造任务分配方法。
所述存储器可以由任何类型的易失性或非易失性存储设备或者它们的组合实现，例如静态随机存取存储器(Static Random Access Memery，简称SRAM)，电可擦除可编程只读存储器(Electrically Erasable Programmable Read-Only Memory，简称EEPROM),可擦除可编程只读存储器(Erasable Programmable Read-Only Memory，简称EPROM),可编程只读存储器(Programmable Read-Only Memory，简称PROM),只读存储器(Read-Only Memory，简称ROM)，磁存储器，快闪存储器，磁盘或光盘。
本实施例还提供一种计算机可读存储介质。在本公开各个实施例中的各功能 单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。所述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。
基于这样的理解，本公开的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本公开各个实施例所述方法的全部或部分步骤。
而前述的存储介质包括：闪存、硬盘、多媒体卡、卡型存储器(例如，SD或DX存储器等)、随机访问存储器(RAM)、静态随机访问存储器(SRAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、可编程只读存储器(PROM)、磁性存储器、磁盘、光盘、服务器、APP应用商城等等各种可以存储程序校验码的介质，其上存储有计算机程序，所述计算机程序被处理器执行时可以实现如下方法步骤：
步骤01:获取订单需求，将所述订单需求分解成多个任务需求；
步骤02:基于所述任务需求得到完成每个任务的时间成本和经济成本；
步骤03:基于所有任务的所述时间成本和所述经济成本得到完成订单的总时间成本和总经济成本；
步骤04:对每个任务的所述时间成本和所述经济成本、订单的所述总时间成本和所述总经济成本进行优化，以进行资源配置。
具体的实施方式和产生的效果可以参考上述实施例中所述，本公开在此不再赘述。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本公开的范围。所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统、装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在本公开所提供的几个实施例中，应该理解到，所揭露的系统、装置和方法， 可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
以上结合具体实施例描述了本公开的基本原理，但是，需要指出的是，在本公开中提及的优点、优势、效果等仅是示例而非限制，不能认为这些优点、优势、效果等是本公开的各个实施例必须具备的。另外，上述公开的具体细节仅是为了示例的作用和便于理解的作用，而非限制，上述细节并不限制本公开为必须采用上述具体的细节来实现。
本公开中涉及的器件、装置、设备、系统的方框图仅作为例示性的例子并且不意图要求或暗示必须按照方框图示出的方式进行连接、布置、配置。如本领域技术人员将认识到的，可以按任意方式连接、布置、配置这些器件、装置、设备、系统。
还需要指出的是，在本公开的装置、设备和方法中，各部件或各步骤是可以分解和/或重新组合的。这些分解和/或重新组合应视为本公开的等效方案。
提供所公开的方面的以上描述以使本领域的任何技术人员能够做出或者使用本公开。对这些方面的各种修改对于本领域技术人员而言是非常显而易见的，并且在此定义的一般原理可以应用于其他方面而不脱离本公开的范围。因此，本公开不意图被限制到在此示出的方面，而是按照与在此公开的原理和新颖的特征一致的最宽范围。
本公开的描述中，“多个”的含义是至少两个，例如两个，三个等，除非另有明确具体的限定。本公开实施例中所有方向性指示(诸如上、下、左、右、前、后、顶、底……)仅用于解释在某一特定姿态(如附图所示)下各部件之间的相对位置关系、运动情况等，如果该特定姿态发生改变时，则该方向性指示也相应地随之改变。此外，术语“包括”和“具有”以及它们任何变形，意图在于覆盖不 排他的包含。例如包含了一系列步骤或单元的过程、方法、系统、产品或设备没有限定于已列出的步骤或单元，而是可选地还包括没有列出的步骤或单元，或可选地还包括对于这些过程、方法、产品或设备固有的其它步骤或单元。
另外，在本文中提及“实施例”意味着，结合实施例描述的特定特征、结构或特性可以包含在本公开的至少一个实施例中。在说明书中的各个位置出现该短语并不一定均是指相同的实施例，也不是与其它实施例互斥的独立的或备选的实施例。本领域技术人员显式地和隐式地理解的是，本文所描述的实施例可以与其它实施例相结合。
以上所述，仅为本公开的具体实施方式，但本公开的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本公开揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本公开的保护范围之内。因此，本公开的保护范围应以权利要求的保护范围为准。以上所述仅为本公开的较佳实施例而已，并不用以限制本公开，凡在本公开的精神和原则之内，所作的任何修改、等同替换等，均应包含在本公开的保护范围之内。

Claims (10)

  1. 一种多因素约束下面向多式联运的制造任务分配方法，包括：
    获取订单需求，将所述订单需求分解成多个任务需求；
    基于所述任务需求得到完成每个任务的时间成本和经济成本；
    基于所有任务的所述时间成本和所述经济成本得到完成订单的总时间成本和总经济成本；
    对每个任务的所述时间成本和所述经济成本、订单的所述总时间成本和所述总经济成本进行优化，以进行资源配置。
  2. 根据权利要求1所述的多因素约束下面向多式联运的制造任务分配方法，其中，所述任务需求包括：采购任务、生产加工任务、仓储任务、转运任务和结算任务中的至少一种。
  3. 根据权利要求1所述的多因素约束下面向多式联运的制造任务分配方法，其中，所述时间成本包括：采购时间、生产时间、仓储时间、转运时间、金融服务时间中的至少一种。
  4. 根据权利要求1所述的多因素约束下面向多式联运的制造任务分配方法，其中，所述经济成本包括：采购成本、生产成本、仓储成本、转运成本、金融服务成本中的至少一种。
  5. 根据权利要求1所述的多因素约束下面向多式联运的制造任务分配方法，其中，基于所有任务的所述时间成本和所述经济成本得到完成订单的总时间成本和总经济成本的步骤包括：基于所有任务的所述时间成本和所述经济成本，在协同关系的约束下得到完成订单的总时间成本和总经济成本。
  6. 根据权利要求5所述的多因素约束下面向多式联运的制造任务分配方法，其中，所述协同关系包括：地域协同关系和时间协同关系中的至少一种。
  7. 根据权利要求1所述的多因素约束下面向多式联运的制造任务分配方法，其中，所述对每个任务的所述时间成本和所述经济成本、订单的所述总时间成本和所述总经济成本进行优化的步骤包括：利用遗传学算法对每个任务的所述时间成本和所述经济成本、订单的所述总时间成本和所述总经济成本进行优化。
  8. 一种多因素约束下面向多式联运的制造任务分配装置，其中，包括：
    获取模块，配置为获取订单需求，将所述订单需求分解成多个任务需求；
    计算模块，配置为基于所述任务需求得到完成每个任务的时间成本和经济成本；基于所有任务的所述时间成本和所述经济成本得到完成订单的总时间成本和总经济成本；
    优化模块，配置为对每个任务的所述时间成本和所述经济成本、订单的所述总时间成本和所述总经济成本进行优化，以进行资源配置。
  9. 一种电子设备，其中，包括存储器和处理器，所述存储器配置为存储一条或多条计算机指令，其中，所述一条或多条计算机指令被所述处理器执行时实现如权利要求1-7中任意一项所述的多因素约束下面向多式联运的制造任务分配方法。
  10. 一种计算机可读存储介质，其中，所述计算机可读存储介质中存储有计算机程序，所述计算机程序被处理器执行时用以实现如权利要求1-7任意一项所述的多因素约束下面向多式联运的制造任务分配方法。
PCT/CN2022/088226 2021-11-12 2022-04-21 多因素约束下面向多式联运的制造任务分配方法及装置 WO2023082549A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202111346102.5A CN114254861A (zh) 2021-11-12 2021-11-12 多因素约束下面向多式联运的制造任务分配方法及装置
CN202111346102.5 2021-11-12

Publications (1)

Publication Number Publication Date
WO2023082549A1 true WO2023082549A1 (zh) 2023-05-19

Family

ID=80790832

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2022/088226 WO2023082549A1 (zh) 2021-11-12 2022-04-21 多因素约束下面向多式联运的制造任务分配方法及装置

Country Status (2)

Country Link
CN (1) CN114254861A (zh)
WO (1) WO2023082549A1 (zh)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114254861A (zh) * 2021-11-12 2022-03-29 珠海格力电器股份有限公司 多因素约束下面向多式联运的制造任务分配方法及装置

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106408113A (zh) * 2016-08-31 2017-02-15 广州亿澳斯软件股份有限公司 生产订单的排产管理方法与系统
US20190049975A1 (en) * 2017-08-11 2019-02-14 Tata Consultancy Services Limited Method and system for optimally allocating warehouse procurement tasks to distributed robotic agents
CN110599057A (zh) * 2019-09-19 2019-12-20 珠海格力电器股份有限公司 订单业务处理方法、集中调度平台及计算机可读存储介质
CN110837918A (zh) * 2019-10-08 2020-02-25 北京航空航天大学 一种多层集成调度机制
CN113112143A (zh) * 2021-04-08 2021-07-13 杭州电子科技大学 云制造环境下多级别制造商协同生产任务分配方法及系统
CN114254861A (zh) * 2021-11-12 2022-03-29 珠海格力电器股份有限公司 多因素约束下面向多式联运的制造任务分配方法及装置

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106408113A (zh) * 2016-08-31 2017-02-15 广州亿澳斯软件股份有限公司 生产订单的排产管理方法与系统
US20190049975A1 (en) * 2017-08-11 2019-02-14 Tata Consultancy Services Limited Method and system for optimally allocating warehouse procurement tasks to distributed robotic agents
CN110599057A (zh) * 2019-09-19 2019-12-20 珠海格力电器股份有限公司 订单业务处理方法、集中调度平台及计算机可读存储介质
CN110837918A (zh) * 2019-10-08 2020-02-25 北京航空航天大学 一种多层集成调度机制
CN113112143A (zh) * 2021-04-08 2021-07-13 杭州电子科技大学 云制造环境下多级别制造商协同生产任务分配方法及系统
CN114254861A (zh) * 2021-11-12 2022-03-29 珠海格力电器股份有限公司 多因素约束下面向多式联运的制造任务分配方法及装置

Also Published As

Publication number Publication date
CN114254861A (zh) 2022-03-29

Similar Documents

Publication Publication Date Title
US10636008B2 (en) Data processing system and method
CN107220789A (zh) 一种物流配送调度方法及系统
CN110472899B (zh) 一种物品的出库分配方法和装置
CN108960733A (zh) 一种基于移动配送车的购物配送方法及系统
US7603354B2 (en) Method for enhancing the operation of a database
CN106156975A (zh) 业务对象的库存信息处理方法及装置
CN105631625A (zh) 物流多供应商订单管理系统及方法
CN108090717A (zh) 一种用于全渠道零售的云仓派单方法
CN109547530A (zh) 区域共识方法、系统及设备
US11842402B2 (en) Fee/rebate contingent order matching system and method
CN107292560A (zh) 物资库存管理方法及系统
WO2023082549A1 (zh) 多因素约束下面向多式联运的制造任务分配方法及装置
WO2014069214A1 (ja) 在庫供給網システム、在庫供給網システムサーバ、在庫供給網システムプログラム
CN111932185B (zh) 一种药品库存调拨系统及方法
CN112184393A (zh) 一种用于互联网电商的订单交易方法
US20140279353A1 (en) C2EX Compute Commodities Exchange
CN117893142A (zh) 海外仓订单配单的方法、系统、电子设备及存储介质
CN109902980A (zh) 用于业务处理的方法及装置
WO2023071374A1 (zh) 货物的数据处理方法及装置
CN113724051B (zh) 信息处理方法、装置、系统、设备及存储介质
CN114997779A (zh) 一种仓储处理方法、装置、电子设备及计算机可读介质
CN107392341A (zh) 箱体预约方法以及系统
CN104205133A (zh) 便携终端管理服务器及便携终端管理程序
CN104067302A (zh) 便携终端管理服务器及便携终端管理程序
JP2021105806A (ja) リサイクル資源取引支援システム

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 22891361

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE