不确定需求下可重构制造流水线配置与生产计划联合优化研究  

Research on Joint Optimization of Reconfigurable Manufacturing Flow Line Configuration and Production Planning under Uncertain Demand

作　　者：崔峰 耿娜 江志斌 周鑫[1] CUI Feng;GENG Na;JIANG Zhibin;ZHOU Xin(Antai College of Economics and Management,Shanghai Jiao Tong University,Shanghai 200030,China;Sino-US Global Logistics Institute,Shanghai Jiao Tong University,Shanghai 200030,China)

机构地区：[1]上海交通大学安泰经济与管理学院,上海200030 [2]上海交通大学中美物流研究院,上海200030

出　　处：《工程管理科技前沿》2024年第2期29-37,共9页Frontiers of Science and Technology of Engineering Management

基　　金：国家自然科学基金重点资助项目(71931007)。

摘　　要：可重构制造系统作为新的智能制造范式,可以通过增加或移除可重构机床的模块提高系统的响应性和灵活性,以更好地应对动态变化的市场环境。配置优化与生产计划的联合优化是影响可重构制造系统效率的重要决策。为了解决这一问题,本文考虑需求的不确定,建立了两阶段随机规划模型,对可重构制造系统进行配置与生产计划的联合决策优化,目标函数是最小化配置成本、重构成本、期望库存和延期成本。为了求解该模型,本文采用Danzig-Wolfe(DW)分解,把原模型转化为集划分问题和定价子问题,设计了基于列生成框架的求解算法。数值算例验证了所提模型和算法的有效性,可以有效帮助企业在可重构制造中进行资源配置和生产计划的决策。In the context of global competition,market demands have become increasingly volatile,with shorter lead times and a wider range of individualized products.These trends have presented significant challenges for intelligent manufacturing systems to adapt and meet customer needs effectively.The reconfigurable manufacturing system(RMS),as a cutting-edge smart manufacturing approach,offers the flexibility to reconfigure its manufacturing capabilities by adjusting machine tools.However,optimizing the configuration of an RMS is a complex task.Unlike traditional manufacturing systems,configuring an RMS requires not only acquiring appropriate machines but also making dynamic decisions in response to shifting demands.This means that the configuration decision is no longer a static one made at the start of production but one that evolves over time.Furthermore,the modularity of machine tools adds another layer of complexity,as reconfiguration decisions involve determining the optimal mix of modules rather than simple increases or decreases in manufacturing capacity.Additionally,determining the optimal configurations for different production processes is a significant challenge.Consequently,solving the configuration optimization problem in RMS is a complex task due to the large number of decision variables.To deal with this problem,this paper considers the uncertain demand and propose a two-stage stochastic programming model with the objective to minimize the configuration cost,the reconfiguration cost,the expected inventory and the deferred cost.The uncertain demand is described by using the sample average approximation(SAA)method.Due to the uncertainty of market demand,the decisions are divided into two stages.The first stage decisions are the configuration and reconfiguration decisions.The former refers to the determination of the number of reconfigurable machine tools on the production line,while the latter refers to the change of the configuration of the reconfigurable machine tools by adding or removing auxiliary module

关 键 词：可重构制造系统 配置优化 不确定需求 列生成 

分 类 号：F402[经济管理—产业经济]