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A fuzzy set approach to activity scheduling for product development

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  • J R Wang

    (Feng Chia University)

Abstract

Industries need to effectively manage their product development processes to reduce the product development time and cost. Due to incomplete design information at the early stage of product development, the duration of each activity is difficult to estimate accurately. The objective of this research is to develop a methodology to schedule product development projects having imprecise temporal information. The research problem is formulated as a fuzzy constraint satisfaction problem and a new method based on possibility theory is proposed to determine the satisfaction degrees of fuzzy temporal constraints. Based on the proposed method, a fuzzy scheduling procedure is developed to construct a schedule with the least possibility of being late and to maximize the satisfaction degrees of all fuzzy temporal constraints. Moreover, the computational efficiency of the proposed approach is also discussed. The proposed methodology can produce more satisfactory schedules in an uncertain product development environment.

Suggested Citation

  • J R Wang, 1999. "A fuzzy set approach to activity scheduling for product development," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(12), pages 1217-1228, December.
    • Handle: RePEc:pal:jorsoc:v:50:y:1999:i:12:d:10.1057_palgrave.jors.2600814
    DOI: 10.1057/palgrave.jors.2600814
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    Citations

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    Cited by:

    1. Herroelen, Willy & Leus, Roel, 2005. "Project scheduling under uncertainty: Survey and research potentials," European Journal of Operational Research, Elsevier, vol. 165(2), pages 289-306, September.
    2. Bhaskar, Tarun & Pal, Manabendra N. & Pal, Asim K., 2011. "A heuristic method for RCPSP with fuzzy activity times," European Journal of Operational Research, Elsevier, vol. 208(1), pages 57-66, January.
    3. 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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