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LSSPER: Solving the Resource-Constrained Project Scheduling Problem with Large Neighbourhood Search

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  • Mireille Palpant
  • Christian Artigues
  • Philippe Michelon

Abstract

This paper presents the Local Search with SubProblem Exact Resolution (LSSPER) method based on large neighbourhood search for solving the resource-constrained project scheduling problem (RCPSP). At each step of the method, a subpart of the current solution is fixed while the other part defines a subproblem solved externally by a heuristic or an exact solution approach (using either constraint programming techniques or mathematical programming techniques). Hence, the method can be seen as a hybrid scheme. The key point of the method deals with the choice of the subproblem to be optimized. In this paper, we investigate the application of the method to the RCPSP. Several strategies for generating the subproblem are proposed. In order to evaluate these strategies, and, also, to compare the whole method with current state-of-the-art heuristics, extensive numerical experiments have been performed. The proposed method appears to be very efficient. Copyright Kluwer Academic Publishers 2004

Suggested Citation

  • Mireille Palpant & Christian Artigues & Philippe Michelon, 2004. "LSSPER: Solving the Resource-Constrained Project Scheduling Problem with Large Neighbourhood Search," Annals of Operations Research, Springer, vol. 131(1), pages 237-257, October.
    • Handle: RePEc:spr:annopr:v:131:y:2004:i:1:p:237-257:10.1023/b:anor.0000039521.26237.62
    DOI: 10.1023/B:ANOR.0000039521.26237.62
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    Cited by:

    1. Polten, Lukas & Emde, Simon, 2021. "Scheduling automated guided vehicles in very narrow aisle warehouses," Omega, Elsevier, vol. 99(C).
    2. 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.
    3. 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.
    4. Debels, D. & Vanhoucke, M., 2006. "Meta-Heuristic resource constrained project scheduling: solution space restrictions and neighbourhood extensions," Vlerick Leuven Gent Management School Working Paper Series 2006-18, Vlerick Leuven Gent Management School.
    5. 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.
    6. Jourdan, L. & Basseur, M. & Talbi, E.-G., 2009. "Hybridizing exact methods and metaheuristics: A taxonomy," European Journal of Operational Research, Elsevier, vol. 199(3), pages 620-629, December.
    7. 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.
    8. 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.
    9. W. Jaśkowski & M. Szubert & P. Gawron, 2016. "A hybrid MIP-based large neighborhood search heuristic for solving the machine reassignment problem," Annals of Operations Research, Springer, vol. 242(1), pages 33-62, July.
    10. Tseng, Lin-Yu & Chen, Shih-Chieh, 2006. "A hybrid metaheuristic for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 175(2), pages 707-721, December.
    11. Arda Turkgenci & Huseyin Guden & Mehmet Gülşen, 2021. "Decomposition based extended project scheduling for make-to-order production," Operational Research, Springer, vol. 21(2), pages 801-825, June.
    12. Zdeněk Hanzálek & Přemysl Šůcha, 2017. "Time symmetry of resource constrained project scheduling with general temporal constraints and take-give resources," Annals of Operations Research, Springer, vol. 248(1), pages 209-237, January.
    13. 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.
    14. 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.
    15. D. Debels & M. Vanhoucke, 2005. "A Decomposition-Based Heuristic For The Resource-Constrained Project Scheduling Problem," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/293, Ghent University, Faculty of Economics and Business Administration.
    16. Estellon, Bertrand & Gardi, Frédéric & Nouioua, Karim, 2008. "Two local search approaches for solving real-life car sequencing problems," European Journal of Operational Research, Elsevier, vol. 191(3), pages 928-944, December.
    17. Jürgen Kuster & Dietmar Jannach & Gerhard Friedrich, 2010. "Applying Local Rescheduling in response to schedule disruptions," Annals of Operations Research, Springer, vol. 180(1), pages 265-282, November.
    18. 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.

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