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

机译:具有随机处理时间和机器故障的多目标流水车间调度研究

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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.
机译:流水车间调度问题通常以单目标确定性方法进行研究,而它们却是多目标的,并且存在很大的不确定性。尽管进化算法通常用于解决多目标和随机问题,但很少有方法将这两个方面结合在一起本文采用随机处理时间和机器故障对多目标流水车间调度问题进行建模,针对最大时间流和最大延迟时间设计了一种数学方案,提出了一种混合多目标遗传算法来解决该优化问题。仿真实验结果表明,该算法可以为不确定条件下的流水车间调度问题提供良好的性能。

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