An improved genetic algorithm with recurrent search for the job-shop scheduling problem

Indexed by:会议论文

Date of Publication:2006-06-21

Included Journals:EI、CPCI-S、Scopus

Volume:1

Page Number:3386-3390

Key Words:recurrent search; genetic algorithm; job-shop; crossover operation

Abstract:A genetic algorithm with some improvement is proposed to avoid the local optimum for job-shop scheduling problem (JSP). There is recurrent searching process of genetic operation in the improved genetic algorithm. The improved crossover operation can shake current population from local optimum in genetic algorithm. The recurrent crossover operation and mutation operation can inherit excellent characteristics from parent chromosomes and accelerate the diversity of offspring. Both benchmark FT(6x6) and LA1(10x5) job-shop scheduling problems are used to show the effectiveness of the proposed method. Experimental results demonstrate that the proposed genetic algorithm does not get stuck at a local optimum easily, and it is fast in convergence, simple to be implemented.

Date of Publication:2006-06-21