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

机译:工艺序列灵活性的求职调度问题的改进遗传算法

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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:本文的重点是考虑到古典作业商店调度问题(SFJSP)中的序列灵活性的新调度问题,这在大多数现实情况下非常实际.SFJSP包括两个正在确定每个作业的灵活操作序列的子问题根据所确定的操作序列测序机器上的所有操作。提出了改进的遗传算法(IGA)以解决该问题以最小化Makespan。为IGA提出了改进的染色体编码模式,其中添加了基于序列的表示段。对于基于一般的操作的代表段。相应的交叉和突变运算符旨在确保为SFJSP产生可行的后代染色体。所提出的算法的有效性和效率是通过计算实验对轴承制造公司的四个实际情况进行的计算实验测试。

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