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A Formulation for the Stochastic Multi-Mode Resource-Constrained Project Scheduling Problem Solved with a Multi-Start Iterated Local Search Metaheuristic

Author

Listed:
  • Alfredo S. Ramos

    (Facultad de Ingeniería, Universidad Panamericana, Zapopan 45010, Jalisco, Mexico)

  • Pablo A. Miranda-Gonzalez

    (Departamento de Ingeniería Industrial, Universidad Católica del Norte, Antofagasta 1270709, Chile)

  • Samuel Nucamendi-Guillén

    (Facultad de Ingeniería, Universidad Panamericana, Zapopan 45010, Jalisco, Mexico)

  • Elias Olivares-Benitez

    (Facultad de Ingeniería, Universidad Panamericana, Zapopan 45010, Jalisco, Mexico)

Abstract

This research introduces a stochastic version of the multi-mode resource-constrained project scheduling problem (MRCPSP) and its mathematical model. In addition, an efficient multi-start iterated local search (MS-ILS) algorithm, capable of solving the deterministic MRCPSP, is adapted to deal with the proposed stochastic version of the problem. For its deterministic version, the MRCPSP is an NP-hard optimization problem that has been widely studied. The problem deals with a trade-off between the amount of resources that each project activity requires and its duration. In the case of the proposed stochastic formulation, the execution times of the activities are uncertain. Benchmark instances of projects with 10, 20, 30, and 50 activities from well-known public libraries were adapted to create test instances. The adapted algorithm proved to be capable and efficient for solving the proposed stochastic problem.

Suggested Citation

  • Alfredo S. Ramos & Pablo A. Miranda-Gonzalez & Samuel Nucamendi-Guillén & Elias Olivares-Benitez, 2023. "A Formulation for the Stochastic Multi-Mode Resource-Constrained Project Scheduling Problem Solved with a Multi-Start Iterated Local Search Metaheuristic," Mathematics, MDPI, vol. 11(2), pages 1-25, January.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:2:p:337-:d:1029369
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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.
    2. Sönke Hartmann, 2001. "Project Scheduling with Multiple Modes: A Genetic Algorithm," Annals of Operations Research, Springer, vol. 102(1), pages 111-135, February.
    3. 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.
    4. Hartmann, Sonke & Kolisch, Rainer, 2000. "Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 127(2), pages 394-407, December.
    5. 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.
    6. F. Brian Talbot, 1982. "Resource-Constrained Project Scheduling with Time-Resource Tradeoffs: The Nonpreemptive Case," Management Science, INFORMS, vol. 28(10), pages 1197-1210, October.
    7. Balouka, Noemie & Cohen, Izack, 2021. "A robust optimization approach for the multi-mode resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 291(2), pages 457-470.
    8. Hartmann, Sönke & Drexl, Andreas, 1997. "Project scheduling with multiple modes: A comparison of exact algorithms," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 430, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    9. Sprecher, Arno & Kolisch, Rainer & Drexl, Andreas, 1995. "Semi-active, active, and non-delay schedules for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 80(1), pages 94-102, January.
    10. 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.
    11. Elloumi, Sonda & Fortemps, Philippe, 2010. "A hybrid rank-based evolutionary algorithm applied to multi-mode resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 205(1), pages 31-41, August.
    12. Sprecher, Arno & Drexl, Andreas, 1998. "Multi-mode resource-constrained project scheduling by a simple, general and powerful sequencing algorithm," European Journal of Operational Research, Elsevier, vol. 107(2), pages 431-450, June.
    13. Slowinski, Roman & Soniewicki, Boleslaw & Weglarz, Jan, 1994. "DSS for multiobjective project scheduling," European Journal of Operational Research, Elsevier, vol. 79(2), pages 220-229, December.
    14. M. Urgo & J. Váncza, 2019. "A branch-and-bound approach for the single machine maximum lateness stochastic scheduling problem to minimize the value-at-risk," Flexible Services and Manufacturing Journal, Springer, vol. 31(2), pages 472-496, June.
    15. Joanna Józefowska & Marek Mika & Rafał Różycki & Grzegorz Waligóra & Jan Węglarz, 2001. "Simulated Annealing for Multi-Mode Resource-Constrained Project Scheduling," Annals of Operations Research, Springer, vol. 102(1), pages 137-155, February.
    16. 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.
    17. T Wauters & K Verbeeck & G Vanden Berghe & P De Causmaecker, 2011. "Learning agents for the multi-mode project scheduling problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(2), pages 281-290, February.
    18. Guidong Zhu & Jonathan F. Bard & Gang Yu, 2006. "A Branch-and-Cut Procedure for the Multimode Resource-Constrained Project-Scheduling Problem," INFORMS Journal on Computing, INFORMS, vol. 18(3), pages 377-390, August.
    19. 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.
    20. Erik L. Demeulemeester & Willy S. Herroelen, 1997. "New Benchmark Results for the Resource-Constrained Project Scheduling Problem," Management Science, INFORMS, vol. 43(11), pages 1485-1492, November.
    21. Ranjbar, Mohammad & De Reyck, Bert & Kianfar, Fereydoon, 2009. "A hybrid scatter search for the discrete time/resource trade-off problem in project scheduling," European Journal of Operational Research, Elsevier, vol. 193(1), pages 35-48, February.
    22. Hartmann, Sönke & Kolisch, R., 2000. "Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 11180, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    23. Wen-Huei Yang & Kamlesh Mathur & Ronald H. Ballou, 2000. "Stochastic Vehicle Routing Problem with Restocking," Transportation Science, INFORMS, vol. 34(1), pages 99-112, February.
    24. 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.
    25. 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.
    26. Mori, Masao & Tseng, Ching Chih, 1997. "A genetic algorithm for multi-mode resource constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 100(1), pages 134-141, July.
    27. Paul, Jomon A. & Zhang, Minjiao, 2019. "Supply location and transportation planning for hurricanes: A two-stage stochastic programming framework," European Journal of Operational Research, Elsevier, vol. 274(1), pages 108-125.
    28. Pellerin, Robert & Perrier, Nathalie & Berthaut, François, 2020. "A survey of hybrid metaheuristics for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 280(2), pages 395-416.
    29. 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.
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