会议专题

Research on Multiobjective Flow Shop Scheduling with Stochastic Processing Times and Machine Breakdowns

Flow-shop scheduling problems are generally studied in a single-objective deterministic way whereas they are multiobjective and are subjected to a wide range of uncertainties.Although evolutionary algorithms are commonly used to solve multiobjective and stochastic problems,very few approaches combine simultaneously these two aspects.In the paper the multiobjective flow shop scheduling problem is modeled with the stochastic processing time and the machine breakdown.A mathematical scheme is designed for the largest flow of time and the largest delay time.A hybrid multiobjective genetic algorithm is proposed to solve the optimization problems iteratively on uncertain condition.The results of simulation experiments are shown that the algorithm can provide a good performance for the flow shop scheduling problems on the uncertain condition.

flow shop scheduling uncertainty multiobjective combinatorial optimization genetic algorithm stochastic processing times

Qiang Zhou Xunxue Cui

Department of Computer Science and TechnologyChuzhou UniversityChuzhou,China New Star Research Institute of Applied Technology Hefei,China

国际会议

2008 IEEE International Conference on Service Operations and Logistics, and Informatics(IEEE/SOLI’2008)(IEEE服务运作、物流与信息年会)

北京

英文

2008-10-12(万方平台首次上网日期,不代表论文的发表时间)