基于SPEA的多目标柔性作业车间调度方法  

Multi-objective Flexible Job-shop Scheduling Based on Strength Pareto Evolutionary Algorithm

作　　者：王云[1] 谭建荣[2] 冯毅雄[1] 李中凯[1] 

机构地区：[1]浙江大学流体传动及控制国家重点实验室,杭州310027 [2]浙江大学CAD&CG国家重点实验室,杭州310027

出　　处：《中国机械工程》2010年第10期1167-1172,共6页China Mechanical Engineering

基　　金：国家863高技术研究发展计划资助项目(2007AA04Z190);国家自然科学基金资助项目(50505044;60573175)

摘　　要：研究了多目标柔性作业车间调度问题,构建了以制造工期、加工成本及交货期为目标函数的柔性作业车间多目标调度模型,应用改进的强度Pareto进化算法(SPEA)进行求解。在该算法中,引入模糊C-均值聚类(FCM)加快外部种群的聚类过程。采用约束Pareto支配和双层编码策略,一次运行就能够求得Pareto最优解集,并利用模糊集合理论的方法得到Pareto解的优先选择序列和选出一个最优解。最后,将该方法应用于某机械公司车间调度中,验证了该方法的有效性和适应性。To solve FJSP,a multi-objective FJSP optimization model was set up,concerned with time,cost and delivery satisfaction.The optimal solutions were obtained by using improved SPEA.The SPEA was improved by introducing the fuzzy C-means clustering algorithm to accelerate the clustering procedure within the external population.With the constraint Pareto domination concept and the two-level representation schema,a Pareto optimal set could be achieved in a single run.Then the preference sequence of Pareto solutions was achieved and a solution was extracted as the best compromise one based on set theory.The feasibility and validity of the proposed algorithm have been proved by the results in a workshop scheduling.

关 键 词：柔性车间调度问题 多目标优化 SPEA 多目标决策方法 

分 类 号：TH166[机械工程—机械制造及自动化]