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Multi-mode resource constrained pro ject scheduling using RCPSP and SAT solvers

Author

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  • J. COELHO
  • M. VANHOUCKE

Abstract

This paper reports on a new solution approach for the well-known multi-mode resource-constrained project scheduling problem (MMRCPSP). This problem type aims at the selection of a single activity mode from a set of available modes in order to construct a precedence and a (renewable and non-renewable) resource feasible project schedule with a minimal makespan. The problem type is known to be NPhard and has been solved using various exact as well as (meta-)heuristic procedures. The new algorithm splits the problem type into a mode assignment and a single mode project scheduling step. The mode assignment step is solved by a satisfiability (SAT) problem solver and returns a feasible mode selection to the project scheduling step. The project scheduling step is solved using a efficient meta-heuristic procedure from literature to solve the resource-constrained project scheduling problem (RCPSP). However, unlike many traditional meta-heuristic methods in literature to solve the MMRCPSP, the new approach executes these two steps in one run, relying on a single priority list. Straightforward adaptations to the pure SAT solver by using pseudo boolean non-renewable resource constraints has led to a high quality solution approach in a reasonable computational time. Computational results show that the PSPLIB problem instances can be solved better than the current best procedures from literature.

Suggested Citation

  • J. Coelho & M. Vanhoucke, 2009. "Multi-mode resource constrained pro ject scheduling using RCPSP and SAT solvers," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 09/614, Ghent University, Faculty of Economics and Business Administration.
  • Handle: RePEc:rug:rugwps:09/614
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    1. Hartmann, Sönke & Briskorn, Dirk, 2022. "An updated survey of variants and extensions of the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 297(1), pages 1-14.
    2. Ilkyeong Moon & Sanghyup Lee & Moonsoo Shin & Kwangyeol Ryu, 2016. "Evolutionary resource assignment for workload-based production scheduling," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 375-388, April.
    3. Gutjahr, Walter J., 2015. "Bi-Objective Multi-Mode Project Scheduling Under Risk Aversion," European Journal of Operational Research, Elsevier, vol. 246(2), pages 421-434.
    4. Angione, Claudio & Occhipinti, Annalisa & Stracquadanio, Giovanni & Nicosia, Giuseppe, 2013. "Bose–Einstein condensation in satisfiability problems," European Journal of Operational Research, Elsevier, vol. 227(1), pages 44-54.
    5. Nima Zoraghi & Aria Shahsavar & Babak Abbasi & Vincent Peteghem, 2017. "Multi-mode resource-constrained project scheduling problem with material ordering under bonus–penalty policies," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 49-79, April.
    6. Messelis, Tommy & De Causmaecker, Patrick, 2014. "An automatic algorithm selection approach for the multi-mode resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 233(3), pages 511-528.
    7. Luis F. Machado-Domínguez & Carlos D. Paternina-Arboleda & Jorge I. Vélez & Agustin Barrios-Sarmiento, 2021. "A memetic algorithm to address the multi-node resource-constrained project scheduling problem," Journal of Scheduling, Springer, vol. 24(4), pages 413-429, August.
    8. Guillermo Campos Ciro & Frédéric Dugardin & Farouk Yalaoui & Russell Kelly, 2016. "Open shop scheduling problem with a multi-skills resource constraint: a genetic algorithm and an ant colony optimisation approach," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4854-4881, August.
    9. Bruno Vieira & Derya Demirtas & Jeroen B. Kamer & Erwin W. Hans & Louis-Martin Rousseau & Nadia Lahrichi & Wim H. Harten, 2020. "Radiotherapy treatment scheduling considering time window preferences," Health Care Management Science, Springer, vol. 23(4), pages 520-534, December.
    10. Alireza Etminaniesfahani & Hanyu Gu & Leila Moslemi Naeni & Amir Salehipour, 2024. "An efficient relax-and-solve method for the multi-mode resource constrained project scheduling problem," Annals of Operations Research, Springer, vol. 338(1), pages 41-68, July.
    11. Vanhoucke, Mario & Coelho, José, 2016. "An approach using SAT solvers for the RCPSP with logical constraints," European Journal of Operational Research, Elsevier, vol. 249(2), pages 577-591.
    12. Zamani, Reza, 2013. "A competitive magnet-based genetic algorithm for solving the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 229(2), pages 552-559.
    13. Tamara Borreguero Sanchidrián & Tom Portoleau & Christian Artigues & Alvaro García Sánchez & Miguel Ortega Mier & Pierre Lopez, 2024. "Large neighborhood search for an aeronautical assembly line time-constrained scheduling problem with multiple modes and a resource leveling objective," Annals of Operations Research, Springer, vol. 338(1), pages 13-40, July.
    14. Martin Josef Geiger & Sandra Huber & Sebastian Langton & Marius Leschik & Christian Lindorf & Ulrich Tüshaus, 2018. "Multi-attribute assignment of trains to departures in rolling stock management," Annals of Operations Research, Springer, vol. 271(2), pages 1131-1163, December.
    15. Van Peteghem, Vincent & Vanhoucke, Mario, 2014. "An experimental investigation of metaheuristics for the multi-mode resource-constrained project scheduling problem on new dataset instances," European Journal of Operational Research, Elsevier, vol. 235(1), pages 62-72.
    16. Gómez Sánchez, Mariam & Lalla-Ruiz, Eduardo & Fernández Gil, Alejandro & Castro, Carlos & Voß, Stefan, 2023. "Resource-constrained multi-project scheduling problem: A survey," European Journal of Operational Research, Elsevier, vol. 309(3), pages 958-976.
    17. Kasapidis, Gregory A. & Paraskevopoulos, Dimitris C. & Mourtos, Ioannis & Repoussis, Panagiotis P., 2025. "A unified solution framework for flexible job shop scheduling problems with multiple resource constraints," European Journal of Operational Research, Elsevier, vol. 320(3), pages 479-495.
    18. Servranckx, Tom & Coelho, José & Vanhoucke, Mario, 2024. "A genetic algorithm for the Resource-Constrained Project Scheduling Problem with Alternative Subgraphs using a boolean satisfiability solver," European Journal of Operational Research, Elsevier, vol. 316(3), pages 815-827.
    19. Geiger, Martin Josef, 2017. "A multi-threaded local search algorithm and computer implementation for the multi-mode, resource-constrained multi-project scheduling problem," European Journal of Operational Research, Elsevier, vol. 256(3), pages 729-741.
    20. Zahid, Taiba & Kühn, Mathias & Völker, Michael & Schmidt, Thorsten, 2015. "Investigation of Scheduling Techniques for Uncertain Conditions," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Blecker, Thorsten & Kersten, Wolfgang & Ringle, Christian M. (ed.), Operational Excellence in Logistics and Supply Chains: Optimization Methods, Data-driven Approaches and Security Insights. Proceedings of the Hamburg , volume 22, pages 171-202, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    21. He, Naihui & Zhang, David Z. & Yuce, Baris, 2022. "Integrated multi-project planning and scheduling - a multiagent approach," European Journal of Operational Research, Elsevier, vol. 302(2), pages 688-699.

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