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Survey on fuzzy shop scheduling

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  • J. Behnamian

    (Bu-Ali Sina University)

Abstract

The real life scheduling problems often have several uncertainties. The solutions of these problems can provide deeper insights to the decision maker than those of deterministic problems. Fuzzy set theory as most important tool to model uncertainty represents an attractive tool to aid research in the production management. Since to the best of our knowledge, there is not a comprehensive review on the fuzzy scheduling literature, the goal of this paper is to provide an extensive review for the fuzzy machine scheduling which it covers more than 140 papers. For this purpose, first, this paper classifies and reviews the literature according to shop environments, including single machine, parallel machines, flowshop, job shop and open shop. Then the reviewed literature is quantified and measured. At the end the paper concludes by presenting some problems receiving less attention than the others and proposing some research opportunities in the field.

Suggested Citation

  • J. Behnamian, 2016. "Survey on fuzzy shop scheduling," Fuzzy Optimization and Decision Making, Springer, vol. 15(3), pages 331-366, September.
    • Handle: RePEc:spr:fuzodm:v:15:y:2016:i:3:d:10.1007_s10700-015-9225-5
    DOI: 10.1007/s10700-015-9225-5
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    References listed on IDEAS

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    1. Jinliang Cheng & Hiroshi Kise & Hironori Matsumoto, 1997. "A branch-and-bound algorithm with fuzzy inference for a permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 96(3), pages 578-590, February.
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    6. Sanja Petrovic & Carole Fayad & Dobrila Petrovic & Edmund Burke & Graham Kendall, 2008. "Fuzzy job shop scheduling with lot-sizing," Annals of Operations Research, Springer, vol. 159(1), pages 275-292, March.
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    16. Anglani, Alfredo & Grieco, Antonio & Guerriero, Emanuela & Musmanno, Roberto, 2005. "Robust scheduling of parallel machines with sequence-dependent set-up costs," European Journal of Operational Research, Elsevier, vol. 161(3), pages 704-720, March.
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    2. Yaliang Wang & Xinyu Fan & Chendi Ni & Kanghong Gao & Shousong Jin, 2023. "Collaborative optimization of workshop layout and scheduling," Journal of Scheduling, Springer, vol. 26(1), pages 43-59, February.

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