Abstract: Key equipment shop that serves for multiple Original Equipment Manufacturers (OEMs) is characterized by strong requirement traceability,multiple product type,high process flexibility,fluctuating workloads and complex assembly structures.The production scheduling of key equipment shop is closely related to its part outsourcing and progress coordination decisions,while the majority of related works focus on separate decisions and weaken the correlation between decisions.In this study,key equipment shop schedulingis abstracted as an integration of with part sharing and outsourcing decision in Flexible Assembly Job Shop Problem (FAJSP),and a mixed integrated programming model was established for FAJSP.Next,part outsourcing and sharing decisions were respectively incorporated into the encoding and decoding scheme of Genetic algorithm (GA),which was considered as a algorithm with excellent global search capability.Then a iterated greedy search algorithm with extinguished local search capability was introduced into GA,and a Genetic Algorithm with Iterated Greedy search (GAIG) was customized designed for FAJSP solving.Finally,simulation experiments were conducted in a number of generalized instances,and the results in various dimensions validated the effectiveness and usability of our proposed algorithm.A sensitivity analysis of the algorithm was carried out in test cases under differentiated scenarios.

Key words: flexible assembly jobshop scheduling, part sharing, part outsourcing, meta-heuristics algorithm

摘要： 服务于多个主机厂的关键配套车间具有需求跟随性强、产品类型多、资源柔性程度高、生产负荷波动、关联零件难齐套等特点,其中涉及的生产调度、零件外协与齐套控制等决策问题存在紧密关联性,现有研究大多专注于单方面决策而弱化了其间关联性。为此,抽象出一类集成零件外协与共享决策的柔性装配作业车间调度问题,针对此类问题构建了混合整数规划模型,再结合问题特征设计了一类遗传迭代贪心算法,其将零件外协与共享决策分别集成到全局搜索能力强的遗传算法的编码和解码中,并与局部搜索能力强的迭代贪心搜索算法进行有效混合。从实际生产环境提取出一般化算例进行实验,各维度结果展示了算法的可用性和有效性,并通过设置差异化场景实验进行了算法的适应性分析。

关键词: 柔性装配作业车间调度, 零件共享, 零件外协, 元启发式算法