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Accessing feasible space in a generalized job shop scheduling problem with the fuzzy processing times: a fuzzy-neural approach

Author

Listed:
  • R Tavakkoli-Moghaddam

    (University of Tehran)

  • N Safaei

    (Iran University of Science and Technology)

  • M M O Kah

    (Abti-American University of Nigeria, Yola, Nigeria and American University)

Abstract

This paper presents a fuzzy-neural approach for constraint satisfaction of a generalized job shop scheduling problem (GJSSP) fuzzy processing times. Our study is an extension of recently developed research in a GJSSP where the processing time of operations was constant. Our paper assumes that the processing time of jobs is uncertain. The proposed fuzzy-neural approach can be adaptively adjusted with weights of connections based on sequence resource and uncertain processing time constraints of the GJSSP during its processing. The computational results show that the proposed neural approach is able to find good solutions in reasonable time.

Suggested Citation

  • R Tavakkoli-Moghaddam & N Safaei & M M O Kah, 2008. "Accessing feasible space in a generalized job shop scheduling problem with the fuzzy processing times: a fuzzy-neural approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(4), pages 431-442, April.
    • Handle: RePEc:pal:jorsoc:v:59:y:2008:i:4:d:10.1057_palgrave.jors.2602351
    DOI: 10.1057/palgrave.jors.2602351
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    References listed on IDEAS

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    1. McCahon, Cynthia S. & Lee, E. Stanley, 1992. "Fuzzy job sequencing for a flow shop," European Journal of Operational Research, Elsevier, vol. 62(3), pages 294-301, November.
    2. Ishii, Hiroaki & Tada, Minoru, 1995. "Single machine scheduling problem with fuzzy precedence relation," European Journal of Operational Research, Elsevier, vol. 87(2), pages 284-288, December.
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    Cited by:

    1. Yuri N. Sotskov & Natalja M. Matsveichuk & Vadzim D. Hatsura, 2020. "Schedule Execution for Two-Machine Job-Shop to Minimize Makespan with Uncertain Processing Times," Mathematics, MDPI, vol. 8(8), pages 1-51, August.
    2. Wong, Bo K. & Lai, Vincent S., 2011. "A survey of the application of fuzzy set theory in production and operations management: 1998-2009," International Journal of Production Economics, Elsevier, vol. 129(1), pages 157-168, January.

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