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A hybrid genetic algorithm/mathematical programming approach to the multi-family flowshop scheduling problem with lot streaming

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  • Martin, Clarence H

Abstract

This paper presents a hybrid genetic algorithm/mathematical programming heuristic for the n-job, m-machine flowshop problems with lot streaming. The number of sublots for each job and the size of sublots are directly addressed by the heuristic and setups may be sequence-dependent. A new aspect of the problem, the interleaving of sublots from different jobs in the processing sequence, is developed and addressed. Computational results from 12 randomly generated test sets of 24 problems each are presented.

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  • Martin, Clarence H, 2009. "A hybrid genetic algorithm/mathematical programming approach to the multi-family flowshop scheduling problem with lot streaming," Omega, Elsevier, vol. 37(1), pages 126-137, February.
    • Handle: RePEc:eee:jomega:v:37:y:2009:i:1:p:126-137
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    Cited by:

    1. Pan, Quan-Ke & Ruiz, Rubén, 2012. "An estimation of distribution algorithm for lot-streaming flow shop problems with setup times," Omega, Elsevier, vol. 40(2), pages 166-180, April.
    2. Tzu-Li Chen & Chen-Yang Cheng & Yi-Han Chou, 2020. "Multi-objective genetic algorithm for energy-efficient hybrid flow shop scheduling with lot streaming," Annals of Operations Research, Springer, vol. 290(1), pages 813-836, July.
    3. Gribkovskaia, Irina V. & Kovalev, Sergey & Werner, Frank, 2010. "Batching for work and rework processes on dedicated facilities to minimize the makespan," Omega, Elsevier, vol. 38(6), pages 522-527, December.
    4. Lin, Yi-Kuei & Yeh, Cheng-Ta, 2012. "Determining the optimal double-component assignment for a stochastic computer network," Omega, Elsevier, vol. 40(1), pages 120-130, January.
    5. Karapetyan, Daniel & Mitrovic Minic, Snezana & Malladi, Krishna T. & Punnen, Abraham P., 2015. "Satellite downlink scheduling problem: A case study," Omega, Elsevier, vol. 53(C), pages 115-123.

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