Genetic Algorithms for a Job-Shop Scheduling Problem.

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  • Nakagami Masahito
    Research Laboratory of Resources Utilization, Tokyo Institute of Technology
  • Ishida Masaru
    Research Laboratory of Resources Utilization, Tokyo Institute of Technology

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  • 遺伝的アルゴリズムによるスケジューリング問題の解法
  • イデンテキ アルゴリズム ニヨル スケジューリング モンダイ ノ カイホウ

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Abstract

We propose the following genetic algorithms (GA) to effectively solve job-shop scheduling problems by introducing the following judgments of the present status of the genes in the population and characteristics of the task sequence : (1) Extracting excellent genes, i.e., the effective part in the string from individuals with good fitness ; (2) Exploiting local search around an elite by checking all probable mutation within one Hamming distance ; (3) Introducing an overrule to examine only the cases which seem to give good results.<BR>These algorithms are tested by applying them to the Muth-Thompson Job-Shop Scheduling Problems (1963), and we prove that the application of GA with combined use of these algorithms can generate practically good schedules even for job-shop scheduling problems of relatively large scale.

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