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A multi-threaded local search algorithm and computer implementation for the multi-mode, resource-constrained multi-project scheduling problem

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  • Geiger, Martin Josef

Abstract

The article describes a solution approach for the multi-mode, resource-constrained multi-project scheduling problem. Our key ideas are based on the concepts of Variable Neighborhood Search, together with Iterated Local Search. A particular focus of this work is devoted towards the parallel implementation of such local search solution techniques. With the increasing availability of parallel (multi-core) computer hardware, we believe that such techniques are about to gain attractiveness in the future.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:256:y:2017:i:3:p:729-741
    DOI: 10.1016/j.ejor.2016.07.024
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    References listed on IDEAS

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    1. Lova, Antonio & Tormos, Pilar & Cervantes, Mariamar & Barber, Federico, 2009. "An efficient hybrid genetic algorithm for scheduling projects with resource constraints and multiple execution modes," International Journal of Production Economics, Elsevier, vol. 117(2), pages 302-316, February.
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    3. 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.
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    6. Weglarz, Jan & Józefowska, Joanna & Mika, Marek & Waligóra, Grzegorz, 2011. "Project scheduling with finite or infinite number of activity processing modes - A survey," European Journal of Operational Research, Elsevier, vol. 208(3), pages 177-205, February.
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    9. Coelho, José & Vanhoucke, Mario, 2011. "Multi-mode resource-constrained project scheduling using RCPSP and SAT solvers," European Journal of Operational Research, Elsevier, vol. 213(1), pages 73-82, August.
    10. Martin Geiger, 2012. "Applying the threshold accepting metaheuristic to curriculum based course timetabling," Annals of Operations Research, Springer, vol. 194(1), pages 189-202, April.
    11. Bouleimen, K. & Lecocq, H., 2003. "A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version," European Journal of Operational Research, Elsevier, vol. 149(2), pages 268-281, September.
    12. J Alcaraz & C Maroto & R Ruiz, 2003. "Solving the Multi-Mode Resource-Constrained Project Scheduling Problem with genetic algorithms," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(6), pages 614-626, June.
    13. Hartmann, Sönke & Briskorn, Dirk, 2010. "A survey of variants and extensions of the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 207(1), pages 1-14, November.
    14. Geiger, Martin Josef, 2010. "On heuristic search for the single machine total weighted tardiness problem - Some theoretical insights and their empirical verification," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1235-1243, December.
    15. Peteghem, Vincent Van & Vanhoucke, Mario, 2010. "A genetic algorithm for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 201(2), pages 409-418, March.
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    Citations

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    Cited by:

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    2. 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.
    3. 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.
    4. 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.
    5. Yukang He & Tao Jia & Weibo Zheng, 2024. "Simulated annealing for centralised resource-constrained multiproject scheduling to minimise the maximal cash flow gap under different payment patterns," Annals of Operations Research, Springer, vol. 338(1), pages 115-149, July.
    6. Bredael, Dries & Vanhoucke, Mario, 2023. "Multi-project scheduling: A benchmark analysis of metaheuristic algorithms on various optimisation criteria and due dates," European Journal of Operational Research, Elsevier, vol. 308(1), pages 54-75.
    7. Maryam Sadeghloo & Saeed Emami & Ali Divsalar, 2024. "A Benders decomposition algorithm for the multi-mode resource-constrained multi-project scheduling problem with uncertainty," Annals of Operations Research, Springer, vol. 339(3), pages 1637-1677, August.
    8. Abdollah Arasteh, 2020. "Considering Project Management Activities for Engineering Design Groups," SN Operations Research Forum, Springer, vol. 1(4), pages 1-29, December.
    9. 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.
    10. Wuliang Peng & Jiali lin & Jingwen Zhang & Liangwei Chen, 2022. "A bi-objective hierarchical program scheduling problem and its solution based on NSGA-III," Annals of Operations Research, Springer, vol. 308(1), pages 389-414, January.
    11. Felix Hübner & Patrick Gerhards & Christian Stürck & Rebekka Volk, 2021. "Solving the nuclear dismantling project scheduling problem by combining mixed-integer and constraint programming techniques and metaheuristics," Journal of Scheduling, Springer, vol. 24(3), pages 269-290, June.
    12. Arben Ahmeti & Nysret Musliu, 2025. "Hybridizing constraint programming and meta-heuristics for multi-mode resource-constrained multiple projects scheduling Problem," Journal of Heuristics, Springer, vol. 31(1), pages 1-37, March.
    13. Rob Eynde & Mario Vanhoucke, 2020. "Resource-constrained multi-project scheduling: benchmark datasets and decoupled scheduling," Journal of Scheduling, Springer, vol. 23(3), pages 301-325, June.
    14. Patrick Gerhards, 2020. "The multi-mode resource investment problem: a benchmark library and a computational study of lower and upper bounds," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(4), pages 901-933, December.
    15. Shen-Tsu Wang, 2018. "An Analysis of the Optimal Customer Clusters Using Dynamic Multi-Objective Decision," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 547-582, March.

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