The Fuzzy Job-Shop Scheduling Based on Improved Genetic Algorithm

Author

Liu, Wen-yuan ; Chen, Zhi-Ru ; Shi, Yan ; Yang, Hai-Ying

Author_Institution

Yan Shan Univ., Qinhuangdao

Volume

6

fYear

2007

fDate

19-22 Aug. 2007

Firstpage

3144

Lastpage

3147

Abstract

To improve the performance of the existing genetic algorithms for job shop scheduling problem and speed up searching for optimal scheduling solution, this paper analyzes the difficulty and characteristics of the operation-based coding and designs a new crossover, which is based on the job. As illustrative numerical examples, both 6times6 and 10 times 10 job-shop scheduling problems are considered. Through the comparative simulations with position-based crossover, the feasibility and effectiveness of the proposed crossover are demonstrated.

Keywords

computer integrated manufacturing; fuzzy set theory; genetic algorithms; integrated manufacturing systems; job shop scheduling; fuzzy job shop scheduling; genetic algorithm; operation-based coding; optimal scheduling solution; position-based crossover; Algorithm design and analysis; Cybernetics; Design engineering; Genetic algorithms; Genetic engineering; Information science; Job shop scheduling; Machine learning; Optimal scheduling; Production; Genetic algorithms; Job crossover; Job-Shop scheduling;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2007 International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-0973-0

Electronic_ISBN

978-1-4244-0973-0

Type

conf

DOI

10.1109/ICMLC.2007.4370688

Filename

4370688