A genetic algorithm embedded with a concise chromosome representation for distributed and flexible job-shop scheduling problems
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DOI: 10.1007/s10845-015-1083-z
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- Kacem, Imed & Hammadi, Slim & Borne, Pierre, 2002. "Pareto-optimality approach for flexible job-shop scheduling problems: hybridization of evolutionary algorithms and fuzzy logic," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 60(3), pages 245-276.
- Stéphane Dauzère-Pérès & Jan Paulli, 1997. "An integrated approach for modeling and solving the general multiprocessor job-shop scheduling problem using tabu search," Annals of Operations Research, Springer, vol. 70(0), pages 281-306, April.
- De Giovanni, L. & Pezzella, F., 2010. "An Improved Genetic Algorithm for the Distributed and Flexible Job-shop Scheduling problem," European Journal of Operational Research, Elsevier, vol. 200(2), pages 395-408, January.
- M. R. Garey & D. S. Johnson & Ravi Sethi, 1976. "The Complexity of Flowshop and Jobshop Scheduling," Mathematics of Operations Research, INFORMS, vol. 1(2), pages 117-129, May.
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Cited by:
- Guangchen Wang & Peng Wang & Honggang Zhang, 2024. "A Self-Adaptive Memetic Algorithm for Distributed Job Shop Scheduling Problem," Mathematics, MDPI, vol. 12(5), pages 1-16, February.
- Guiliang Gong & Raymond Chiong & Qianwang Deng & Qiang Luo, 2020. "A memetic algorithm for multi-objective distributed production scheduling: minimizing the makespan and total energy consumption," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1443-1466, August.
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Keywords
Genetic algorithm; Distributed flexible job-shop; Chromosome representation; Chromosome space; Solution space; Shadow chromosomes;All these keywords.
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