IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i12p1873-d1415883.html
   My bibliography  Save this article

An Agile Adaptive Biased-Randomized Discrete-Event Heuristic for the Resource-Constrained Project Scheduling Problem

Author

Listed:
  • Xabier A. Martin

    (Research Center on Production Management and Engineering, Universitat Politècnica de València, Plaza Ferrandiz-Carbonell, 03801 Alcoy, Spain)

  • Rosa Herrero

    (TecnoCampus, Universitat Pompeu Fabra, Av. Ernest Lluch, 32, 08302 Mataró, Spain)

  • Angel A. Juan

    (Research Center on Production Management and Engineering, Universitat Politècnica de València, Plaza Ferrandiz-Carbonell, 03801 Alcoy, Spain)

  • Javier Panadero

    (Department of Computer Architecture and Operating Systems, Universitat Autònoma de Barcelona, Carrer de les Sitges, 08193 Bellaterra, Spain)

Abstract

In industries such as aircraft or train manufacturing, large-scale manufacturing companies often manage several complex projects. Each of these projects includes multiple tasks that share a set of limited resources. Typically, these tasks are also subject to time dependencies among them. One frequent goal in these scenarios is to minimize the makespan, or total time required to complete all the tasks within the entire project. Decisions revolve around scheduling these tasks, determining the sequence in which they are processed, and allocating shared resources to optimize efficiency while respecting the time dependencies among tasks. This problem is known in the scientific literature as the Resource-Constrained Project Scheduling Problem (RCPSP). Being an NP-hard problem with time dependencies and resource constraints, several optimization algorithms have already been proposed to tackle the RCPSP. In this paper, a novel discrete-event heuristic is introduced and later extended into an agile biased-randomized algorithm complemented with an adaptive capability to tune the parameters of the algorithm. The results underscore the effectiveness of the algorithm in finding competitive solutions for this problem within short computing times.

Suggested Citation

  • Xabier A. Martin & Rosa Herrero & Angel A. Juan & Javier Panadero, 2024. "An Agile Adaptive Biased-Randomized Discrete-Event Heuristic for the Resource-Constrained Project Scheduling Problem," Mathematics, MDPI, vol. 12(12), pages 1-21, June.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:12:p:1873-:d:1415883
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/12/1873/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/12/1873/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. Krüger, Doreen & Scholl, Armin, 2009. "A heuristic solution framework for the resource constrained (multi-)project scheduling problem with sequence-dependent transfer times," European Journal of Operational Research, Elsevier, vol. 197(2), pages 492-508, September.
    3. 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.
    4. Klein, Robert, 1999. "Project scheduling under time-varying resource constraints," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 14075, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. Valls, Vicente & Ballestin, Francisco & Quintanilla, Sacramento, 2008. "A hybrid genetic algorithm for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 185(2), pages 495-508, March.
    6. Valls, Vicente & Ballestin, Francisco & Quintanilla, Sacramento, 2005. "Justification and RCPSP: A technique that pays," European Journal of Operational Research, Elsevier, vol. 165(2), pages 375-386, September.
    7. Debels, Dieter & De Reyck, Bert & Leus, Roel & Vanhoucke, Mario, 2006. "A hybrid scatter search/electromagnetism meta-heuristic for project scheduling," European Journal of Operational Research, Elsevier, vol. 169(2), pages 638-653, March.
    8. Rainer Kolisch & Arno Sprecher & Andreas Drexl, 1995. "Characterization and Generation of a General Class of Resource-Constrained Project Scheduling Problems," Management Science, INFORMS, vol. 41(10), pages 1693-1703, October.
    9. 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.
    10. François Berthaut & Robert Pellerin & Adnène Hajji & Nathalie Perrier, 2018. "A path relinking-based scatter search for the resource-constrained project scheduling problem," International Journal of Project Organisation and Management, Inderscience Enterprises Ltd, vol. 10(1), pages 1-36.
    11. Sönke Hartmann, 2002. "A self‐adapting genetic algorithm for project scheduling under resource constraints," Naval Research Logistics (NRL), John Wiley & Sons, vol. 49(5), pages 433-448, August.
    12. 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.
    13. 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.
    14. 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.
    15. Pilar Tormos & Antonio Lova, 2001. "A Competitive Heuristic Solution Technique for Resource-Constrained Project Scheduling," Annals of Operations Research, Springer, vol. 102(1), pages 65-81, February.
    16. 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.
    17. van der Beek, T. & Souravlias, D. & van Essen, J.T. & Pruyn, J. & Aardal, K., 2024. "Hybrid differential evolution algorithm for the resource constrained project scheduling problem with a flexible project structure and consumption and production of resources," European Journal of Operational Research, Elsevier, vol. 313(1), pages 92-111.
    18. 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.
    19. Dieter Debels & Mario Vanhoucke, 2007. "A Decomposition-Based Genetic Algorithm for the Resource-Constrained Project-Scheduling Problem," Operations Research, INFORMS, vol. 55(3), pages 457-469, June.
    20. Kolisch, Rainer & Hartmann, Sonke, 2006. "Experimental investigation of heuristics for resource-constrained project scheduling: An update," European Journal of Operational Research, Elsevier, vol. 174(1), pages 23-37, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. André Schnabel & Carolin Kellenbrink & Stefan Helber, 2018. "Profit-oriented scheduling of resource-constrained projects with flexible capacity constraints," Business Research, Springer;German Academic Association for Business Research, vol. 11(2), pages 329-356, September.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Valls, Vicente & Ballestin, Francisco & Quintanilla, Sacramento, 2008. "A hybrid genetic algorithm for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 185(2), pages 495-508, March.
    7. 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.
    8. 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.
    9. Kreter, Stefan & Rieck, Julia & Zimmermann, Jürgen, 2016. "Models and solution procedures for the resource-constrained project scheduling problem with general temporal constraints and calendars," European Journal of Operational Research, Elsevier, vol. 251(2), pages 387-403.
    10. 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.
    11. 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.
    12. Yang-Kuei Lin & Chin Soon Chong, 2017. "Fast GA-based project scheduling for computing resources allocation in a cloud manufacturing system," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1189-1201, June.
    13. Zhenyuan Liu & Lei Xiao & Jing Tian, 2016. "An activity-list-based nested partitions algorithm for resource-constrained project scheduling," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4744-4758, August.
    14. 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.
    15. Kellenbrink, Carolin & Helber, Stefan, 2015. "Scheduling resource-constrained projects with a flexible project structure," European Journal of Operational Research, Elsevier, vol. 246(2), pages 379-391.
    16. Kolisch, Rainer & Hartmann, Sonke, 2006. "Experimental investigation of heuristics for resource-constrained project scheduling: An update," European Journal of Operational Research, Elsevier, vol. 174(1), pages 23-37, October.
    17. Amadeu A. Coco & Christophe Duhamel & Andréa Cynthia Santos, 2020. "Modeling and solving the multi-period disruptions scheduling problem on urban networks," Annals of Operations Research, Springer, vol. 285(1), pages 427-443, February.
    18. Sepehr Proon & Mingzhou Jin, 2011. "A genetic algorithm with neighborhood search for the resource‐constrained project scheduling problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(2), pages 73-82, March.
    19. Osman Hürol Türkakın & David Arditi & Ekrem Manisalı, 2021. "Comparison of Heuristic Priority Rules in the Solution of the Resource-Constrained Project Scheduling Problem," Sustainability, MDPI, vol. 13(17), pages 1-17, September.
    20. Dieter Debels & Mario Vanhoucke, 2007. "A Decomposition-Based Genetic Algorithm for the Resource-Constrained Project-Scheduling Problem," Operations Research, INFORMS, vol. 55(3), pages 457-469, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2024:i:12:p:1873-:d:1415883. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.