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Uncertain chance-constrained programming model for project scheduling problem

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  • Xiao Wang
  • Yufu Ning

Abstract

In this paper, we consider an uncertain project scheduling problem, in which activity durations, with no historical data generally, are estimated by belief degrees and assumed to be uncertain variables. To achieve different management goals, we build three uncertain chance-constrained programming models for project scheduling problem, in which the chance constraint must reach a predetermined confidence level. Moreover, these models can all be transformed to their crisp forms, and an intelligent algorithm is designed to search the optimal schedule. Finally, a numerical example is presented to illustrate the usefulness of the proposed model.

Suggested Citation

  • Xiao Wang & Yufu Ning, 2018. "Uncertain chance-constrained programming model for project scheduling problem," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(3), pages 384-391, March.
    • Handle: RePEc:taf:tjorxx:v:69:y:2018:i:3:p:384-391
    DOI: 10.1057/s41274-016-0122-2
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    Cited by:

    1. Hazır, Öncü & Ulusoy, Gündüz, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," International Journal of Production Economics, Elsevier, vol. 223(C).
    2. Öncü Hazir & Gündüz Ulusoy, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," Post-Print hal-02898162, HAL.

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