Optimisation of distributed manufacturing flexible job shop scheduling by using hybrid genetic algorithms
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Industrial and Manufacturing Engineering,Software
Link
http://link.springer.com/content/pdf/10.1007/s10845-015-1084-y.pdf
Reference34 articles.
1. AitZai, A., Benmedjdoub, B., & Boudhar, M. (2014). Branch-and-bound and PSO algorithms for no-wait job shop scheduling. Journal of Intelligent Manufacturing. doi: 10.1007/s10845-014-0906-7
2. Behnamian, J., & Fatemi Ghomi, S. M. T. (2014). A survey of multi-factory scheduling. Journal of Intelligent Manufacturing. doi: 10.1007/s10845-014-0890-y
3. Brandimarte, P. (1993). Routing and scheduling in a flexible job shop by tabu search. Annals of Operations Research, 41(3), 157–183. doi: 10.1007/BF02023073 .
4. 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(2), 364–371. doi: 10.1016/j.eswa.2005.04.009 .
5. Chan, F. T. S., Chung, S. H., Chan, L. Y., Finke, G., & Tiwari, M. K. (2006). Solving distributed FMS scheduling problems subject to maintenance: Genetic algorithms approach. Robotics and Computer-Integrated Manufacturing, 22(5–6), 493–504. doi: 10.1016/j.rcim.2005.11.005 .
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