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Machine learning assisted Differential Evolution for the Dynamic Resource Constrained Multi-project Scheduling Problem with Static project Schedules

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  • van der Beek, T.
  • van Essen, J.T.
  • Pruyn, J.
  • Aardal, K.

Abstract

In large modular construction projects, such as shipbuilding, multiple similar projects arrive stochastically. At project arrival, a schedule has to be created, in which future modifications are difficult and/or undesirable. Since all projects use the same set of shared resources, current scheduling decisions influence future scheduling possibilities. To model this problem, we introduce the Dynamic Resource Constrained Multi-project Scheduling Problem with Static project Schedules. To find schedules, both a greedy approach and simulation-based approach with varying scenarios are introduced. Although the simulation-based approach schedules projects proactively, the computing times are long, even for small instances. Therefore, a method is introduced that learns from schedules obtained in the simulation-based method and uses a neural network to estimate the objective function value. It is shown that this method achieves a significant improvement in objective function value over the greedy algorithm, while only requiring a fraction of the computation time of the simulation-based method.

Suggested Citation

  • van der Beek, T. & van Essen, J.T. & Pruyn, J. & Aardal, K., 2025. "Machine learning assisted Differential Evolution for the Dynamic Resource Constrained Multi-project Scheduling Problem with Static project Schedules," European Journal of Operational Research, Elsevier, vol. 327(3), pages 808-819.
    • Handle: RePEc:eee:ejores:v:327:y:2025:i:3:p:808-819
    DOI: 10.1016/j.ejor.2025.05.059
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    References listed on IDEAS

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    1. A. Alan B. Pritsker & Lawrence J. Waiters & Philip M. Wolfe, 1969. "Multiproject Scheduling with Limited Resources: A Zero-One Programming Approach," Management Science, INFORMS, vol. 16(1), pages 93-108, September.
    2. Sönke Hartmann, 2015. "Time-Varying Resource Requirements and Capacities," International Handbooks on Information Systems, in: Christoph Schwindt & Jürgen Zimmermann (ed.), Handbook on Project Management and Scheduling Vol.1, edition 127, chapter 0, pages 163-176, Springer.
    3. 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.
    4. Satyajith Amaran & Nikolaos V. Sahinidis & Bikram Sharda & Scott J. Bury, 2016. "Simulation optimization: a review of algorithms and applications," Annals of Operations Research, Springer, vol. 240(1), pages 351-380, May.
    5. Li, K. Y. & Willis, R. J., 1992. "An iterative scheduling technique for resource-constrained project scheduling," European Journal of Operational Research, Elsevier, vol. 56(3), pages 370-379, February.
    6. Vanhoucke, Mario & Coelho, Jose & Debels, Dieter & Maenhout, Broos & Tavares, Luis V., 2008. "An evaluation of the adequacy of project network generators with systematically sampled networks," European Journal of Operational Research, Elsevier, vol. 187(2), pages 511-524, June.
    7. M. Berke Pamay & Kerem Bülbül & Gündüz Ulusoy, 2014. "Dynamic Resource Constrained Multi-Project Scheduling Problem with Weighted Earliness/Tardiness Costs," International Series in Operations Research & Management Science, in: P. Simin Pulat & Subhash C. Sarin & Reha Uzsoy (ed.), Essays in Production, Project Planning and Scheduling, edition 127, chapter 10, pages 219-247, Springer.
    8. Juan, Angel A. & Faulin, Javier & Grasman, Scott E. & Rabe, Markus & Figueira, Gonçalo, 2015. "A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems," Operations Research Perspectives, Elsevier, vol. 2(C), pages 62-72.
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