A genetic algorithm embedded with a concise chromosome representation for distributed and flexible job-shop scheduling problems-Reference-Cited by-同舟云学术

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A genetic algorithm embedded with a concise chromosome representation for distributed and flexible job-shop scheduling problems

Published:2015-05-05 Issue:1 Volume:29 Page:19-34
ISSN:0956-5515
Container-title:Journal of Intelligent Manufacturing
language:en
Short-container-title:J Intell Manuf

Author:

Lu Po-Hsiang,Wu Muh-Cherng,Tan Hao,Peng Yong-Han,Chen Chen-Fu

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Industrial and Manufacturing Engineering,Software

Link

http://link.springer.com/content/pdf/10.1007/s10845-015-1083-z.pdf

Reference38 articles.

1. Baykasoǧlu, A. (2002). Linguistic-based meta-heuristic optimization model for flexible job shop scheduling. International Journal of Production Research, 40(17), 4523–4543.

2. Bożejko, W., Uchroński, M., & Wodecki, M. (2010). Parallel hybrid metaheuristics for the flexible job shop problem. Computers & Industrial Engineering, 59, 323–333.

3. Brandimarte, P. (1993). Routing and scheduling in a flexible job shop by tabu search. Annals of Operations Research, 41, 157–183.

4. Bruker, P., & Schlie, R. (1990). Job-shop scheduling with multi-purpose machines. Computing, 45, 369–375.

5. Chan, F. T. S., Chung, S. H., & Chan, P. L. Y. (2005). An adaptive genetic algorithm with dominated genes for distributed scheduling problems. Expert Systems with Applications, 29, 364–371.

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