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An improved multi-objective genetic algorithm for solving flexible job shop problem

机译:一种改进的柔性作业店问题的多目标遗传算法

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In this paper, a solution searching strategy called advanced solution extraction is proposed to assistant multi-objective optimizer for solving flexible job shop problem (FJSP). The goal of this problem is to finish all jobs within minimal critical machine workload, total workload and executing time, simultaneously. For comparing proposed with related work, experiments employ three benchmarks. Each benchmark includes numbers of heterogeneous processors and different jobs for completion. From the results, the proposed method can find more optimal solutions than related work.
机译:在本文中,提出了一种辅助解决方案提取的解决方案策略,用于解决灵活的作业店问题(FJSP)的辅助多目标优化器。此问题的目标是同时在最小的关键机床工作量,总工作量和执行时间内完成所有作业。为了比较相关的工作,实验采用三个基准。每个基准测试包括异构处理器的数量和完成的不同作业。从结果,所提出的方法可以找到比相关工作更优化的解决方案。

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