A genetic algorithm with modified crossover operator and search area adaptation for the job-shop scheduling problem

Authors:
Masato Watanabe;Kenichi Ida;Mitsuo Gen
Affiliations:
Department of SPV, Fuso Engineering Corporation Ltd, Kawasaki 212-0013, Japan;Department of Systems and Information Engineering, Maebashi Institute of Technology, Maebashi 371-0816, Japan;Graduate School of Information, Production and Systems, Waseda University, Kitakyushu 808-0135, Japan
Venue:
Computers and Industrial Engineering - Special issue: Selected papers from the 30th international conference on computers; industrial engineering
Year:
2005

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Abstract

The genetic algorithm with search area adaptation (GSA) has a capacity for adapting to the structure of solution space and controlling the tradeoff balance between global and local searches, even if we do not adjust the parameters of the genetic algorithm (GA), such as crossover and/or mutation rates. But, GSA needs the crossover operator that has ability for characteristic inheritance ratio control. In this paper, we propose the modified genetic algorithm with search area adaptation (mGSA) for solving the Job-shop scheduling problem (JSP). Unlike GSA, our proposed method does not need such a crossover operator. To show the effectiveness of the proposed method, we conduct numerical experiments by using two benchmark problems. It is shown that this method has better performance than existing GAs.