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Planning horizons based proactive rescheduling for stochastic resource-constrained project scheduling problems

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  • Brčić, Mario
  • Katić, Marija
  • Hlupić, Nikica

Abstract

Parties that collaborate on projects need to synchronize their efforts. For this reason they seek a decreased rescheduling variability of the time arrangements. Proactive–reactive scheduling is important in such situations. It predominantly achieves synchronization through a shared baseline schedule and deviation penalties. As the latter currently introduce an unrealistically high level of inflexibility, the solution methods never proactively update the baseline schedule. We propose threshold-based cost functions for the deviation penalties to enable a more realistic modeling of aspects of project collaboration. These functions introduce a greater degree of flexibility through the notion of planning horizons for the activities. This results in the possibility of profitable proactive changes to the baseline schedule. We present two metaheuristic approaches for the case of stochastic durations: rollout-based and iterative policy search. Both these approaches use such opportunities to achieve substantial cost–performance improvements in comparison to the best existing method. This enhancement comes at the price of an increased computational burden and the greater complexity of the solution space.

Suggested Citation

  • Brčić, Mario & Katić, Marija & Hlupić, Nikica, 2019. "Planning horizons based proactive rescheduling for stochastic resource-constrained project scheduling problems," European Journal of Operational Research, Elsevier, vol. 273(1), pages 58-66.
  • Handle: RePEc:eee:ejores:v:273:y:2019:i:1:p:58-66
    DOI: 10.1016/j.ejor.2018.07.037
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    References listed on IDEAS

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    1. Stijn Vonder & Erik Demeulemeester & Roel Leus & Willy Herroelen, 2006. "Proactive-Reactive Project Scheduling Trade-Offs and Procedures," International Series in Operations Research & Management Science, in: Joanna Józefowska & Jan Weglarz (ed.), Perspectives in Modern Project Scheduling, chapter 0, pages 25-51, Springer.
    2. Herroelen, Willy & Leus, Roel, 2005. "Project scheduling under uncertainty: Survey and research potentials," European Journal of Operational Research, Elsevier, vol. 165(2), pages 289-306, September.
    3. Deblaere, Filip & Demeulemeester, Erik & Herroelen, Willy, 2011. "Proactive policies for the stochastic resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 214(2), pages 308-316, October.
    4. Goodson, Justin C. & Thomas, Barrett W. & Ohlmann, Jeffrey W., 2017. "A rollout algorithm framework for heuristic solutions to finite-horizon stochastic dynamic programs," European Journal of Operational Research, Elsevier, vol. 258(1), pages 216-229.
    5. 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.
    6. Kolisch, Rainer & Sprecher, Arno, 1997. "PSPLIB - A project scheduling problem library : OR Software - ORSEP Operations Research Software Exchange Program," European Journal of Operational Research, Elsevier, vol. 96(1), pages 205-216, January.
    7. 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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