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A survey of multi-factory scheduling

Author

Listed:
  • J. Behnamian

    (Bu-Ali Sina University)

  • S. M. T. Fatemi Ghomi

    (Amirkabir University of Technology)

Abstract

Because of current globalization trend, production has shifted from the single factory production to multi-factory production network. To become competitive in today’s rapidly changing market requirements, factories have shifted from a centralized to a more decentralized structure, in many areas of decision making including scheduling. In multi-factory production network, each factory can be considered as an individual entity which has different efficiency and is subject to different constraints, for example, machine advances, worker cost, tax, close to suppliers, and transportation facilities, etc. Since limited resources make scheduling an important decision in the production, for several decades, researchers focused on determining an efficient schedule to improve the productivity. The recent remarkable attention in distributed production management in both academia and the industry has demonstrated the significance of multi-factory scheduling. For the first time, this paper provides a review on the multi-factory machine scheduling. For this, first, the 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 proposes several research opportunities in the field.

Suggested Citation

  • J. Behnamian & S. M. T. Fatemi Ghomi, 2016. "A survey of multi-factory scheduling," Journal of Intelligent Manufacturing, Springer, vol. 27(1), pages 231-249, February.
  • Handle: RePEc:spr:joinma:v:27:y:2016:i:1:d:10.1007_s10845-014-0890-y
    DOI: 10.1007/s10845-014-0890-y
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    References listed on IDEAS

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    3. Ivan Kristianto Singgih & Onyu Yu & Byung-In Kim & Jeongin Koo & Seungdoe Lee, 2020. "Production scheduling problem in a factory of automobile component primer painting," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1483-1496, August.
    4. Ali Gharaei & Fariborz Jolai, 2021. "A Pareto approach for the multi-factory supply chain scheduling and distribution problem," Operational Research, Springer, vol. 21(4), pages 2333-2364, December.
    5. Seyed Ahmad Razavi Al-e-hashem & Ali Papi & Mir Saman Pishvaee & Mohammadreza Rasouli, 2022. "Robust maintenance planning and scheduling for multi-factory production networks considering disruption cost: a bi-objective optimization model and a metaheuristic solution method," Operational Research, Springer, vol. 22(5), pages 4999-5034, November.
    6. Neufeld, Janis S. & Schulz, Sven & Buscher, Udo, 2023. "A systematic review of multi-objective hybrid flow shop scheduling," European Journal of Operational Research, Elsevier, vol. 309(1), pages 1-23.
    7. Perkiss, Stephanie & Bernardi, Cristiana & Dumay, John & Haslam, Jim, 2021. "A sticky chocolate problem: Impression management and counter accounts in the shaping of corporate image," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 81(C).
    8. Jafar-Zanjani, Hamed & Zandieh, Mostafa & Sharifi, Mani, 2022. "Robust and resilient joint periodic maintenance planning and scheduling in a multi-factory network under uncertainty: A case study," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    9. Li, Yantong & Côté, Jean-François & Coelho, Leandro C. & Zhang, Chuang & Zhang, Shuai, 2023. "Order assignment and scheduling under processing and distribution time uncertainty," European Journal of Operational Research, Elsevier, vol. 305(1), pages 148-163.
    10. Mohammed Haoues & Mohammed Dahane & Nadia Kenza Mouss, 2019. "Outsourcing optimization in two-echelon supply chain network under integrated production-maintenance constraints," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 701-725, February.
    11. Ruiz, Rubén & Pan, Quan-Ke & Naderi, Bahman, 2019. "Iterated Greedy methods for the distributed permutation flowshop scheduling problem," Omega, Elsevier, vol. 83(C), pages 213-222.

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