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Robust Project Scheduling

Author

Listed:
  • Demeulemeester, Erik
  • Herroelen, Willy

Abstract

The majority of publications in the extensive literature on resource-constrained project scheduling focus on a static deterministic setting for which a so-called baseline schedule is computed prior to project execution. In the real world, however, a project may be subject to considerable uncertainty. During the actual execution of a project, the baseline schedule may indeed suffer from disruptive events causing the actually realized activity start times to deviate from the predicted start times that were given in the baseline. This text focuses on robust project scheduling, in particular the development of effective and efficient proactive and reactive scheduling procedures. Proactive scheduling aims at generating robust baseline schedules that carry sufficient protection against possible schedule disruptions that may occur during project execution. Reactive scheduling procedures aim at repairing the baseline schedule when the built-in protection fails during the execution of the project. We discuss the fundamentals of state of the art proactive/reactive project scheduling approaches and, along the lines, discuss key directions for future research.

Suggested Citation

  • Demeulemeester, Erik & Herroelen, Willy, 2011. "Robust Project Scheduling," Foundations and Trends(R) in Technology, Information and Operations Management, now publishers, vol. 3(3–4), pages 201-376, January.
    • Handle: RePEc:now:fnttom:0200000021
    DOI: 10.1561/0200000021
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    Citations

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    Cited by:

    1. Peymankar, Mahboobeh & Davari, Morteza & Ranjbar, Mohammad, 2021. "Maximizing the expected net present value in a project with uncertain cash flows," European Journal of Operational Research, Elsevier, vol. 294(2), pages 442-452.
    2. Mengqi Zhao & Xiaoling Wang & Jia Yu & Lei Bi & Yao Xiao & Jun Zhang, 2020. "Optimization of Construction Duration and Schedule Robustness Based on Hybrid Grey Wolf Optimizer with Sine Cosine Algorithm," Energies, MDPI, vol. 13(1), pages 1-17, January.
    3. Min Wang & Guoshan Liu & Xinyu Lin, 2022. "Dynamic Optimization of the Multi-Skilled Resource-Constrained Project Scheduling Problem with Uncertainty in Resource Availability," Mathematics, MDPI, vol. 10(17), pages 1-20, August.
    4. Shichang Xiao & Shudong Sun & Jionghua (Judy) Jin, 2017. "Surrogate Measures for the Robust Scheduling of Stochastic Job Shop Scheduling Problems," Energies, MDPI, vol. 10(4), pages 1-26, April.
    5. Öncü Hazir & Gündüz Ulusoy, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," Post-Print hal-02898162, HAL.
    6. Majid Askarifard & Hamidreza Abbasianjahromi & Mehran Sepehri & Ehsanollah Zeighami, 2021. "A robust multi-objective optimization model for project scheduling considering risk and sustainable development criteria," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 11494-11524, August.
    7. Yangyang Liang & Nanfang Cui & Tian Wang & Erik Demeulemeester, 2019. "Robust resource-constrained max-NPV project scheduling with stochastic activity duration," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(1), pages 219-254, March.
    8. Bing Wang & Xingbao Han & Xianxia Zhang & Shaohua Zhang, 2015. "Predictive-reactive scheduling for single surgical suite subject to random emergency surgery," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 949-966, November.
    9. Xuejun Hu & Jianjiang Wang & Kaijun Leng, 2019. "The Interaction Between Critical Chain Sequencing, Buffer Sizing, and Reactive Actions in a CC/BM Framework," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(03), pages 1-22, June.
    10. D. Laurie Hughes & Nripendra P. Rana & Yogesh K. Dwivedi, 2020. "Elucidation of IS project success factors: an interpretive structural modelling approach," Annals of Operations Research, Springer, vol. 285(1), pages 35-66, February.
    11. 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.
    12. Zdeněk Hanzálek & Přemysl Šůcha, 2017. "Time symmetry of resource constrained project scheduling with general temporal constraints and take-give resources," Annals of Operations Research, Springer, vol. 248(1), pages 209-237, January.
    13. Morteza Davari & Erik Demeulemeester, 2019. "The proactive and reactive resource-constrained project scheduling problem," Journal of Scheduling, Springer, vol. 22(2), pages 211-237, April.
    14. Sleptchenko, Andrei & Al Hanbali, Ahmad & Zijm, Henk, 2018. "Joint planning of service engineers and spare parts," European Journal of Operational Research, Elsevier, vol. 271(1), pages 97-108.
    15. 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.
    16. 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).
    17. Bruni, M.E. & Di Puglia Pugliese, L. & Beraldi, P. & Guerriero, F., 2017. "An adjustable robust optimization model for the resource-constrained project scheduling problem with uncertain activity durations," Omega, Elsevier, vol. 71(C), pages 66-84.
    18. Hongbo Li & Erik Demeulemeester, 2016. "A genetic algorithm for the robust resource leveling problem," Journal of Scheduling, Springer, vol. 19(1), pages 43-60, February.
    19. Masoud Arjmand & Amir Abbas Najafi & Majid Ebrahimzadeh, 2020. "Evolutionary algorithms for multi-objective stochastic resource availability cost problem," OPSEARCH, Springer;Operational Research Society of India, vol. 57(3), pages 935-985, September.

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