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An Electromagnetism Meta-Heuristic For The Resource-Constrained Project Scheduling Problem

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  • D. DEBELS
  • M. VANHOUCKE

Abstract

Recently, a new heuristic algorithm for global optimization has been proposed by Birbil and Fang (2003), referred to as Electromagnetism (EM). This technique is based on the electromagnetism theory of physics, and simulates attraction and repulsion of sample points in order to move towards an optimal solution. In this paper, we have extended the EM methodology for combinatorial optimization problems. To that purpose, we use the EM framework for solving the well-known resource-constrained project scheduling problem (RCPSP) heuristically. We rely on problem-specific characteristics to adapt the original EM framework to the problem under study. We present computational experiments on a standard benchmark dataset, compare the results of the different modifications on the original EM framework with current state-of-the-art heuristics, and show that the procedure is capable of producing consistently good results for challenging instances of the resource-constrained project scheduling problem. We also give directions for future research in order to make the EM framework competitive with the current state-of-the-art heuristics.

Suggested Citation

  • D. Debels & M. Vanhoucke, 2004. "An Electromagnetism Meta-Heuristic For The Resource-Constrained Project Scheduling Problem," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/251, Ghent University, Faculty of Economics and Business Administration.
  • Handle: RePEc:rug:rugwps:04/251
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    File URL: http://wps-feb.ugent.be/Papers/wp_04_251.pdf
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    References listed on IDEAS

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    1. J. Alcaraz & C. Maroto, 2001. "A Robust Genetic Algorithm for Resource Allocation in Project Scheduling," Annals of Operations Research, Springer, vol. 102(1), pages 83-109, February.
    2. 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.
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    Cited by:

    1. V. Van Peteghem & M. Vanhoucke, 2008. "A Genetic Algorithm for the Multi-Mode Resource-Constrained Project Scheduling Problem," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 08/494, Ghent University, Faculty of Economics and Business Administration.
    2. 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.
    3. D. Debels & M. Vanhoucke, 2006. "Meta-heuristic resource-constrained project scheduling:solution space restrictions and neighbourhood extensions," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/387, Ghent University, Faculty of Economics and Business Administration.
    4. 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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    Keywords

    electromagnetism; meta-heuristics; resource-constrained project scheduling;
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