A new genetic coding for job shop scheduling problem considering geno type and pheno type

Authors:
Masaya Yoshikawa;Hideto Nishimura;Hidekazu Terai
Affiliations:
Department of Information Engineering, Meijo University, Nagoya, Aichi, Japan;Department of VLSI System Design, Ritsumeikan University, Kusatsu, Shiga, Japan;Department of VLSI System Design, Ritsumeikan University, Kusatsu, Shiga, Japan
Venue:
CEA'10 Proceedings of the 4th WSEAS international conference on Computer engineering and applications
Year:
2010

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Abstract

Job shop scheduling problem is one of the most important problems in the combinatorial optimization problems, and it is applied to various fields about engineering. Many works have been reported for this problem using Genetic Algorithm (GA). The GA is one of the most powerful optimization methods based on the mechanics of natural evolution. In this paper, we propose a new genetic coding for the job shop scheduling problem. The proposed genetic coding improves the search performance while keeping the run time in comparison with the conventional one. Simulation results using benchmark data prove the validity of the proposed genetic coding comparison with the conventional one.