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Important classes of reactions for the proactive and reactive resource-constrained project scheduling problem

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  • Morteza Davari

    (KU Leuven KULAK
    KU Leuven)

  • Erik Demeulemeester

    (KU Leuven)

Abstract

The proactive and reactive resource-constrained project scheduling problem (PR-RCPSP), that has been introduced recently (Davari and Demeulemeester, 2017), deals with activity duration uncertainty in a very unique way. The optimal solution to an instance of the PR-RCPSP is a proactive and reactive policy (PR-policy) that is a combination of a baseline schedule and a set of required transitions (reactions). In this research, we introduce two interesting classes of reactions, namely the class of selection-based reactions and the class of buffer-based reactions, the latter in fact being a subset of the class of selection-based reactions. We also discuss the theoretical relevance of these two classes of reactions. We run some computational results and report the contributions of the selection-based reactions and the buffer-based reactions in the optimal solution. The results suggest that although both selection-based reactions and buffer-based reactions contribute largely in the construction of the optimal PR-policy, the contribution of the buffer-based reactions is of much greater importance. These results also indicate that the contributions of non-selection-based reactions (reactions that are not selection-based) and selection-but-not-buffer-based reactions (selection-based reactions that are not buffer-based) are very limited.

Suggested Citation

  • Morteza Davari & Erik Demeulemeester, 2019. "Important classes of reactions for the proactive and reactive resource-constrained project scheduling problem," Annals of Operations Research, Springer, vol. 274(1), pages 187-210, March.
    • Handle: RePEc:spr:annopr:v:274:y:2019:i:1:d:10.1007_s10479-018-2899-7
    DOI: 10.1007/s10479-018-2899-7
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    References listed on IDEAS

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    1. Stefan Creemers, 2015. "Minimizing the expected makespan of a project with stochastic activity durations under resource constraints," Working Papers of Department of Decision Sciences and Information Management, Leuven 488396, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven.
    2. Van de Vonder, Stijn & Demeulemeester, Erik & Herroelen, Willy, 2008. "Proactive heuristic procedures for robust project scheduling: An experimental analysis," European Journal of Operational Research, Elsevier, vol. 189(3), pages 723-733, September.
    3. Li, Haitao & Womer, Norman K., 2015. "Solving stochastic resource-constrained project scheduling problems by closed-loop approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 246(1), pages 20-33.
    4. Stefan Creemers, 2015. "Minimizing the expected makespan of a project with stochastic activity durations under resource constraints," Post-Print hal-02992649, HAL.
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    Cited by:

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    4. Nesbitt, Peter & Blake, Lewis R. & Lamas, Patricio & Goycoolea, Marcos & Pagnoncelli, Bernardo K. & Newman, Alexandra & Brickey, Andrea, 2021. "Underground mine scheduling under uncertainty," European Journal of Operational Research, Elsevier, vol. 294(1), pages 340-352.
    5. Balouka, Noemie & Cohen, Izack, 2021. "A robust optimization approach for the multi-mode resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 291(2), pages 457-470.
    6. Younes Aalian & Michel Gamache & Gilles Pesant, 2024. "Short-term underground mine planning with uncertain activity durations using constraint programming," Journal of Scheduling, Springer, vol. 27(5), pages 423-439, October.
    7. Farnaz Torabi Yeganeh & Seyed Hessameddin Zegordi, 2020. "A multi-objective optimization approach to project scheduling with resiliency criteria under uncertain activity duration," Annals of Operations Research, Springer, vol. 285(1), pages 161-196, February.
    8. 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.
    9. Saad Muslet Albogami & Mohd Khairol Anuar Bin Mohd Ariffin & Eris Elianddy Bin Supeni & Kamarul Arifin Ahmad, 2021. "A New Hybrid AHP and Dempster—Shafer Theory of Evidence Method for Project Risk Assessment Problem," Mathematics, MDPI, vol. 9(24), pages 1-30, December.
    10. Ilia Tarasov & Alain Haït & Alexander Lazarev & Olga Battaïa, 2024. "Metric estimation approach for managing uncertainty in resource leveling problem," Annals of Operations Research, Springer, vol. 338(1), pages 645-673, July.
    11. Maziar Khoshsirat & Seyed Meysam Mousavi, 2024. "A new proactive and reactive approach for resource-constrained project scheduling problem under activity and resource disruption: a scenario-based robust optimization approach," Annals of Operations Research, Springer, vol. 338(1), pages 597-643, July.

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