Reinforcement learning iterated greedy algorithm for distributed assembly permutation flowshop scheduling problems
Author:
Funder
Ministry of Science and Technology, Taiwan
Chang Gung Memorial Hospital, Linkou
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12652-022-04392-w.pdf
Reference64 articles.
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3. Chan FTS, Chung SH, Chan PLY (2006) Application of genetic algorithms with dominant genes in a distributed scheduling problem in flexible manufacturing systems. Int J Prod Res 44:523–543
4. Cheng CY, Ying KC, Chen HH, Lu HS (2019) Minimizing makespan in distributed mixed no-idle flowshops. Int J Prod Res 57:48–60
5. De Giovanni L, Pezzella F (2010) An improved genetic algorithm for the distributed and flexible job-shop scheduling problem. Eur J Oper Res 200:395–408
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