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A Hybrid Scatter Search / Electromagnetism Meta-Heuristic for Project Scheduling



  • R. LEUS


In the last few decades, several effective algorithms for solving the resource-constrained project scheduling problem have been proposed. However, the challenging nature of this problem, summarised in its strongly NP-hard status, restricts the effectiveness of exact optimisation to relatively small instances. In this paper, we present a new meta-heuristic for this problem, able to provide near-optimal heuristic solutions. The procedure combines elements from scatter search, a generic population-based evolutionary search method, and a recently introduced heuristic method for the optimisation of unconstrained continuous functions based on an analogy with electromagnetism theory, hereafter referred to as the electromagnetism meta-heuristic. We present computational experiments on standard benchmark datasets, compare the results with current state-ofthe- 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 demonstrate that the algorithm outperforms state-of-the-art existing heuristics.

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Paper provided by Ghent University, Faculty of Economics and Business Administration in its series Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium with number 04/237.

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Length: 26 pages
Date of creation: Mar 2004
Date of revision:
Handle: RePEc:rug:rugwps:04/237
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  1. Kolisch, Rainer, 1996. "Serial and parallel resource-constrained project scheduling methods revisited: Theory and computation," European Journal of Operational Research, Elsevier, vol. 90(2), pages 320-333, April.
  2. Aristide Mingozzi & Vittorio Maniezzo & Salvatore Ricciardelli & Lucio Bianco, 1998. "An Exact Algorithm for the Resource-Constrained Project Scheduling Problem Based on a New Mathematical Formulation," Management Science, INFORMS, vol. 44(5), pages 714-729, May.
  3. 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.
  4. Valls, Vicente & Quintanilla, Sacramento & Ballestin, Francisco, 2003. "Resource-constrained project scheduling: A critical activity reordering heuristic," European Journal of Operational Research, Elsevier, vol. 149(2), pages 282-301, September.
  5. 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.
  6. 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).
  7. 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.
  8. Taillard, Eric D. & Gambardella, Luca M. & Gendreau, Michel & Potvin, Jean-Yves, 2001. "Adaptive memory programming: A unified view of metaheuristics," European Journal of Operational Research, Elsevier, vol. 135(1), pages 1-16, November.
  9. Fleszar, Krzysztof & Hindi, Khalil S., 2004. "Solving the resource-constrained project scheduling problem by a variable neighbourhood search," European Journal of Operational Research, Elsevier, vol. 155(2), pages 402-413, June.
  10. Erik Demeulemeester & Willy Herroelen, 1992. "A Branch-and-Bound Procedure for the Multiple Resource-Constrained Project Scheduling Problem," Management Science, INFORMS, vol. 38(12), pages 1803-1818, December.
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