Neighborhood structures for genetic local search algorithms

Author

Murata, Tadahiko ; Ishibuchi, Hisao ; Gen, Mitsuo

Author_Institution

Dept. of Ind. & Syst. Eng., Ashikaga Inst. of Technol., Japan

Volume

2

fYear

1998

fDate

21-23 Apr 1998

Firstpage

259

Abstract

We examine the performance of a genetic local search (GLS) algorithm for flowshop scheduling problems. The GLS is a hybrid algorithm of a local search and a genetic algorithm. We have already modified the local search procedure in order to improve the performance of the GLS. In the modified local search procedure, all the neighborhood solutions are not examined. The performance of the GLS is not sensitive to the choice of parameter values such as the crossover probability and the mutation probability. That is the main advantage of the GLS. In this paper, we examine the relation between a mutation operator and a local search procedure. By computer simulations on flowshop scheduling problems, we find that a shift change is appropriate for the local search procedure in the GLS

Keywords

genetic algorithms; probability; production control; search problems; crossover; flowshop scheduling; genetic algorithm; genetic local search algorithms; mutation; neighborhood structures; probability; production control; Computer simulation; Genetic algorithms; Genetic engineering; Genetic mutations; Industrial engineering; Job shop scheduling; Processor scheduling; Scheduling algorithm; Systems engineering and theory; Yttrium;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge-Based Intelligent Electronic Systems, 1998. Proceedings KES '98. 1998 Second International Conference on

Conference_Location

Adelaide, SA

Print_ISBN

0-7803-4316-6

Type

conf

DOI

10.1109/KES.1998.725920

Filename

725920