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The improved genetic algorithm for job-shop scheduling problem with process sequence flexibility

机译:具有过程序列灵活性的改进型车间作业调度遗传算法

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This paper is focused on a new scheduling problem considering the sequence flexibility in classical job shop scheduling problem (SFJSP) that is very practical in most realistic situations.SFJSP consists of two sub-problems which are determining the sequence of flexible operations of each job and sequencing all the operations on the machines according to the determined operation sequence.An improved genetic algorithm (IGA) is proposed to solve this problem to minimize makespan.An improved chromosome encoding schema is proposed for IGA,in which sequence-based representation segment is added to the general operation-based representation segment.The corresponding crossover and mutation operators are designed to ensure the generation of feasible offspring chromosome for SFJSP.The effectiveness and efficiency of the proposed algorithm is tested by computational experiments on four practical instances of a bearing manufacturing corporation.
机译:本文关注的是一个新的调度问题,它考虑了经典作业车间调度问题(SFJSP)中的序列灵活性,这在大多数现实情况下都非常实用.SFJSP包含两个子问题,这些子问题确定了每个作业的灵活操作的顺序,并且根据确定的操作顺序对机器上的所有操作进行排序。提出了一种改进的遗传算法(IGA)来解决此问题,以最大程度地减少生成时间。提出了一种改进的IGA染色体编码方案,其中添加了基于序列的表示段设计了相应的交叉和变异算子,以确保生成SFJSP可行的后代染色体。通过对轴承制造公司的四个实际实例进行计算实验,验证了该算法的有效性和效率。

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