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A heuristic method for RCPSP with fuzzy activity times

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  • Bhaskar, Tarun
  • Pal, Manabendra N.
  • Pal, Asim K.

Abstract

In this paper, we propose a heuristic method for resource constrained project scheduling problem with fuzzy activity times. This method is based on priority rule for parallel schedule generation scheme. Calculation of critical path in this case requires comparison of fuzzy numbers. Distance based ranking of fuzzy number is used for finding the critical path length and concept of shifting criticality is proposed for some of the special cases. We also propose a measure for finding the non-integer power of a fuzzy number. We discuss some properties of the proposed method. We use an example to illustrate the method.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:208:y:2011:i:1:p:57-66
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    References listed on IDEAS

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    1. Hartmann, Sonke & Kolisch, Rainer, 2000. "Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 127(2), pages 394-407, December.
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    5. 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.
    6. Hartmann, Sönke & Kolisch, R., 2000. "Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 11180, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
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    Cited by:

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    2. Yuvraj Gajpal & Ashraf Elazouni, 2015. "Enhanced heuristic for finance-based scheduling of construction projects," Construction Management and Economics, Taylor & Francis Journals, vol. 33(7), pages 531-553, July.
    3. Seddik, Yasmina & Hanzálek, Zdenek, 2017. "Match-up scheduling of mixed-criticality jobs: Maximizing the probability of jobs execution," European Journal of Operational Research, Elsevier, vol. 262(1), pages 46-59.
    4. Yagub Alipouri & Mohammad Hassan Sebt & Abdollah Ardeshir & Mohammad Hossein Fazel Zarandi, 2020. "A mixed-integer linear programming model for solving fuzzy stochastic resource constrained project scheduling problem," Operational Research, Springer, vol. 20(1), pages 197-217, March.
    5. Portoleau, Tom & Artigues, Christian & Guillaume, Romain, 2024. "Robust decision trees for the multi-mode project scheduling problem with a resource investment objective and uncertain activity duration," European Journal of Operational Research, Elsevier, vol. 312(2), pages 525-540.
    6. Malek Masmoudi & Erwin W. Hans & Alain Haït, 2016. "Tactical project planning under uncertainty: fuzzy approach," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 10(3), pages 301-322.
    7. Zhao, Mingxuan & Zhou, Jian & Wang, Ke & Pantelous, Athanasios A., 2023. "Project scheduling problem with fuzzy activity durations: A novel operational law based solution framework," European Journal of Operational Research, Elsevier, vol. 306(2), pages 519-534.

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