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A Decomposition-Based Heuristic For The Resource-Constrained Project Scheduling Problem

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  • D. DEBELS

    ()

  • M. VANHOUCKE

    ()

Abstract

In the last few decades the resource-constrained project scheduling problem has become a popular problem type in operations research. However, due to its strongly NP-hard status, the effectiveness of exact optimisation procedures is restricted to relatively small instances. In this paper we present a new genetic algorithm (GA) for this problem, able to provide near-optimal heuristic solutions. This GA procedure has been extended by a so-called decomposition-based heuristic (DBH) which iteratively solves subparts of the project. We present computational experiments on two datasets. The first benchmark set is used to illustrate the contribution of both the GA and the DBH. The second set is used to compare the results with current state-of-the-art heuristics, and to show that the procedure is capable of producing consistently good results for challenging instances of the resource-constrained project scheduling problem. We illustrate that GA is currently the best performing RCPSP meta-heuristic, and that the DBH further improves the performance of the GA

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File URL: http://www.feb.ugent.be/nl/Ondz/wp/Papers/wp_05_293.pdf
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Bibliographic Info

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 05/293.

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Length: 29 pages
Date of creation: Feb 2005
Date of revision:
Handle: RePEc:rug:rugwps:05/293

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Related research

Keywords: project scheduling; genetic algorithms; decomposition;

This paper has been announced in the following NEP Reports:

References

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  1. 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.
  2. 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.
  3. Kolisch, R. & Padman, R., 2001. "An integrated survey of deterministic project scheduling," Omega, Elsevier, vol. 29(3), pages 249-272, June.
  4. Brucker, Peter & Drexl, Andreas & Mohring, Rolf & Neumann, Klaus & Pesch, Erwin, 1999. "Resource-constrained project scheduling: Notation, classification, models, and methods," European Journal of Operational Research, Elsevier, vol. 112(1), pages 3-41, January.
  5. 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.
  6. 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.
  7. Kolisch, Rainer & Padman, R., 2001. "An integrated survey of deterministic project scheduling," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 8114, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
  8. Kolisch, Rainer & Hartmann, Sönke, 1999. "Heuristic algorithms for the resource-constrained project scheduling problem: classification and computational analysis," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 10966, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
  9. 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).
  10. 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.
  11. 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.
  12. 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.
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Citations

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Cited by:
  1. 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.
  2. Edgar Gutiérrez Franco & Fernando La Torre Zurita & Gonzalo Mejía Delgadillo, 2007. "A genetic algorithm for the resource constrained project scheduling problem (RCPSP)," Investigación & Desarrollo 0307, Universidad Privada Boliviana, revised Mar 2007.
  3. M. Vanhoucke, 2007. "A genetic algorithm to investigate the trade-off between project lead time and net present value," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/456, Ghent University, Faculty of Economics and Business Administration.

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