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

Yingjie Xing; Zhuqing Wang; Jing Sun; Wanlei Wang

doi:10.1109/WCICA.2006.1712996

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

Yingjie Xing, Zhuqing Wang, Jing Sun, Wanlei Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

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(6×6) and LA1(10×5) 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.

Original language	English
Title of host publication	Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
Pages	3386-3390
Number of pages	5
DOIs	https://doi.org/10.1109/WCICA.2006.1712996
Publication status	Published - 2006 Dec 1
Externally published	Yes
Event	6th World Congress on Intelligent Control and Automation, WCICA 2006 - Dalian, China Duration: 2006 Jun 21 → 2006 Jun 23

Publication series

Name	Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
Volume	1

Conference

Conference	6th World Congress on Intelligent Control and Automation, WCICA 2006
Country	China
City	Dalian
Period	06/6/21 → 06/6/23

Keywords

Crossover operation
Genetic algorithm
Job-shop
Recurrent search

ASJC Scopus subject areas

Control and Systems Engineering
Software
Computer Science Applications

Access to Document

10.1109/WCICA.2006.1712996

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Cite this

Xing, Y., Wang, Z., Sun, J., & Wang, W. (2006). An improved genetic algorithm with recurrent search for the job-shop scheduling problem. In Proceedings of the World Congress on Intelligent Control and Automation (WCICA) (pp. 3386-3390). [1712996] (Proceedings of the World Congress on Intelligent Control and Automation (WCICA); Vol. 1). https://doi.org/10.1109/WCICA.2006.1712996

An improved genetic algorithm with recurrent search for the job-shop scheduling problem. / Xing, Yingjie; Wang, Zhuqing; Sun, Jing; Wang, Wanlei.

Proceedings of the World Congress on Intelligent Control and Automation (WCICA). 2006. p. 3386-3390 1712996 (Proceedings of the World Congress on Intelligent Control and Automation (WCICA); Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Xing, Y, Wang, Z, Sun, J & Wang, W 2006, An improved genetic algorithm with recurrent search for the job-shop scheduling problem. in Proceedings of the World Congress on Intelligent Control and Automation (WCICA)., 1712996, Proceedings of the World Congress on Intelligent Control and Automation (WCICA), vol. 1, pp. 3386-3390, 6th World Congress on Intelligent Control and Automation, WCICA 2006, Dalian, China, 06/6/21. https://doi.org/10.1109/WCICA.2006.1712996

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