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Evolutional Algorithm in Solving Flexible Job Shop Scheduling Problem with Uncertainties

In: Liss 2013

Author

Listed:
  • Yahong Zheng

    (Wuhan University of Technology)

  • Lian Lian

    (Dalian University of Technology)

  • Zaifeng Fu

    (Dalian University of Technology)

  • Khaled Mesghouni

    (LAGIS, UMR CNRS 8219, EcoleCentraledeLille)

Abstract

In recent years, the necessity of considering uncertainty in scheduling problem is recognized by many scholars and practitioners, but there are still not effective methods to deal with uncertainty. This paper focuses on the flexible job shop scheduling problem (FJSP). Uncertainties in FJSP includes many aspects, such as the urgently arrival jobs, the uncertain working condition of the machines, etc. In this paper, we propose an inserting algorithm (IA), which can be used to treat the necessary machine maintenance for reducing unavailability of machines. We use the condition based maintenance (CBM) to reduce unavailability of machines. A problem focused in this paper is the flexible job shop scheduling problem with preventive maintenance (FJSPPM). An inserting algorithm (IA) is utilized to add PM into a preschedule scheme of FJSP which is obtained through an evolutional algorithm. Furthermore, a new better solution for an instance in benchmark of FJSP is obtained.

Suggested Citation

  • Yahong Zheng & Lian Lian & Zaifeng Fu & Khaled Mesghouni, 2015. "Evolutional Algorithm in Solving Flexible Job Shop Scheduling Problem with Uncertainties," Springer Books, in: Runtong Zhang & Zhenji Zhang & Kecheng Liu & Juliang Zhang (ed.), Liss 2013, pages 1009-1015, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-40660-7_151
    DOI: 10.1007/978-3-642-40660-7_151
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    Cited by:

    1. Javad Seif & Mohammad Dehghanimohammadabadi & Andrew Junfang Yu, 2020. "Integrated preventive maintenance and flow shop scheduling under uncertainty," Flexible Services and Manufacturing Journal, Springer, vol. 32(4), pages 852-887, December.

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