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Robust scheduling and robustness measures for the discrete time/cost trade-off problem

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  • HazIr, Öncü
  • Haouari, Mohamed
  • Erel, Erdal

Abstract

Projects are often subject to various sources of uncertainties that have a negative impact on activity durations and costs. Therefore, it is crucial to develop effective approaches to generate robust project schedules that are less vulnerable to disruptions caused by uncontrollable factors. In this paper, we investigate the robust discrete time/cost trade-off problem, which is a multi-mode project scheduling problem with important practical relevance. We introduce surrogate measures that aim at providing an accurate estimate of the schedule robustness. The pertinence of each proposed measure is assessed through computational experiments. Using the insights revealed by the computational study, we propose a two-stage robust scheduling algorithm. Finally, we provide evidence that the proposed approach can be extended to solve a complex robust problem with tardiness penalties and earliness revenues.

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  • HazIr, Öncü & Haouari, Mohamed & Erel, Erdal, 2010. "Robust scheduling and robustness measures for the discrete time/cost trade-off problem," European Journal of Operational Research, Elsevier, vol. 207(2), pages 633-643, December.
  • Handle: RePEc:eee:ejores:v:207:y:2010:i:2:p:633-643
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    References listed on IDEAS

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    Cited by:

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    2. He, Yukang & Jia, Tao & Zheng, Weibo, 2023. "Tabu search for dedicated resource-constrained multiproject scheduling to minimise the maximal cash flow gap under uncertainty," European Journal of Operational Research, Elsevier, vol. 310(1), pages 34-52.
    3. Gabrel, Virginie & Murat, Cécile & Thiele, Aurélie, 2014. "Recent advances in robust optimization: An overview," European Journal of Operational Research, Elsevier, vol. 235(3), pages 471-483.
    4. Xiong, Jian & Xing, Li-ning & Chen, Ying-wu, 2013. "Robust scheduling for multi-objective flexible job-shop problems with random machine breakdowns," International Journal of Production Economics, Elsevier, vol. 141(1), pages 112-126.
    5. Valenko Tadej & Klanšek Uroš, 2017. "An integration of spreadsheet and project management software for cost optimal time scheduling in construction," Organization, Technology and Management in Construction, Sciendo, vol. 9(1), pages 1627-1637, December.
    6. Jonas Ingels & Broos Maenhout, 2017. "Employee substitutability as a tool to improve the robustness in personnel scheduling," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 623-658, July.
    7. Shichang Xiao & Zigao Wu & Hongyan Dui, 2022. "Resilience-Based Surrogate Robustness Measure and Optimization Method for Robust Job-Shop Scheduling," Mathematics, MDPI, vol. 10(21), pages 1-22, October.
    8. Philippe Chrétienne, 2020. "Maximizing the number of jobs scheduled at their baseline starting times in case of machine failures," Journal of Scheduling, Springer, vol. 23(1), pages 135-143, February.
    9. 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).
    10. Öncü Hazir & Gündüz Ulusoy, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," Post-Print hal-02898162, HAL.
    11. Ingels, Jonas & Maenhout, Broos, 2019. "Optimised buffer allocation to construct stable personnel shift rosters," Omega, Elsevier, vol. 82(C), pages 102-117.
    12. Said, Samer S. & Haouari, Mohamed, 2015. "A hybrid simulation-optimization approach for the robust Discrete Time/Cost Trade-off Problem," Applied Mathematics and Computation, Elsevier, vol. 259(C), pages 628-636.
    13. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Frank Werner, 2016. "Schedule robustness analysis with the help of attainable sets in continuous flow problem under capacity disruptions," International Journal of Production Research, Taylor & Francis Journals, vol. 54(11), pages 3397-3413, June.
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    15. Junguang Zhang & Dan Wan, 2021. "Determination of early warning time window for bottleneck resource buffer," Annals of Operations Research, Springer, vol. 300(1), pages 289-305, May.
    16. Gang Xuan & Win-Chin Lin & Shuenn-Ren Cheng & Wei-Lun Shen & Po-An Pan & Chih-Ling Kuo & Chin-Chia Wu, 2022. "A Robust Single-Machine Scheduling Problem with Two Job Parameter Scenarios," Mathematics, MDPI, vol. 10(13), pages 1-17, June.

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