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The Electromagnetism Meta-heuristic Applied to the Resource-Constrained Project Scheduling Problem

  • Conference paper
Artificial Evolution (EA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3871))

Abstract

Recently, an electromagnetism (EM) heuristic has been introduced by Birbil and Fang (2003) to solve unconstrained optimization problems. In this paper, we extend the EM methodology to combinatorial optimization problems and illustrate its effectiveness on the well-known resource-constrained project scheduling problem (RCPSP). 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 problem under study. We also give directions for future research in order to further explore the potential of this new technique.

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References

  1. Alcaraz, J., Maroto, C.: A robust genetic algorithm for resource allocation in project scheduling. Annals of Operations Research 102, 83–109 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  2. Alcaraz, J., Maroto, C., Ruiz, R.: Improving the performance of genetic algorithms for the RCOS problems. In: Proceedings of the Ninth International Workshop on Project Management and Scheduling, Nancy, pp. 40–43 (2004)

    Google Scholar 

  3. Baar, T., Brucker, P., Knust, S.: Tabu-search algorithms and lower bounds for the resource-constrained project scheduling problem, Meta-heuristics: Advances and trends in local search paradigms for optimization, pp. 1–8 (1998)

    Google Scholar 

  4. Birbil, S.I., Fang, S.C.: An electromagnetism-like mechanism for global optimization. Journal of Global Optimization 25, 263–282 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  5. Bouleimen, K., Lecocq, H.: A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version. European Journal of Operational Research 149, 268–281 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  6. Coelho, J., Tavares, L.: Comparative analysis of meta-heuricstics for the resource constrained project scheduling problem, Technical report, Department of Civil Engineering, Instituto Superior Tecnico, Portugal (2003)

    Google Scholar 

  7. Debels, D., De Reyck, B., Leus, R., Vanhoucke, M.: A scatter-search meta-heuristic for the resource-constrained project scheduling problem, European Journal of Operational Research, forthcoming

    Google Scholar 

  8. Hartmann, S.: A competitive genetic algorithm for the resource-constrained project scheduling. Naval Research Logistics 45, 733–750 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  9. Hartmann, S.: A self-adapting genetic algorithm for project scheduling under resource constraints. Naval Research Logistics 49, 433–448 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  10. Hartmann, S., Kolisch, R.: Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem. European Journal of Operational Research 127, 394–407 (2000)

    Article  MATH  Google Scholar 

  11. Klein, R.: Project scheduling with time-varying resource constraints. International Journal of Production Research 38(16), 3937–3952 (2000)

    Article  MATH  Google Scholar 

  12. Kochetov, Y., Stolyar, A.: Evolutionary local search with variable neighbourhood for the resource constrained project scheduling problem. In: Proceedings of the 3rd International Workshop of Computer Science and Information Technologies (2003)

    Google Scholar 

  13. Kolisch, R.: Project scheduling under resource constraints - Efficient heuristics for several problem classes, Physica (1995)

    Google Scholar 

  14. Kolisch, R.: Serial and parallel resource-constrained project scheduling methods revisited: theory and computation. European Journal of Operational Research 43, 23–40 (1996)

    MATH  Google Scholar 

  15. Kolisch, R.: Efficient priority rules for the resource-constrained project scheduling problem. Journal of Operations Management 14, 179–192 (1996)

    Article  Google Scholar 

  16. Kolisch, R., Drexl, A.: Adaptive search for solving hard project scheduling problems. Naval Research Logistics 43, 23–40 (1996)

    Article  MATH  Google Scholar 

  17. Kolisch, R., Hartmann, S.: Heuristic algorithms for solving the resource-constrained project scheduling problem: classification and computational analysis. In: Weglarz, J. (ed.) Project Scheduling - Recent Models, Algorithms and Applications, pp. 147–178. Kluwer Academic Publishers, Boston (1999)

    Google Scholar 

  18. Kolisch, R., Hartmann, S.: Experimental investigation of Heuristics for resource-constrained project scheduling: an update, working paper, Technical University of Munich (2004)

    Google Scholar 

  19. Kolisch, R., Sprecher, A.: PSPLIB - A project scheduling library. European Journal of Operational Research 96, 205–216 (1997)

    Article  MATH  Google Scholar 

  20. Leon, V.J., Ramamoorthy, B.: Strength and adaptability of problem-space based neighbourhoods for resource-constrained scheduling. OR Spektrum 17, 173–182 (1995)

    Article  MATH  Google Scholar 

  21. Li, K.Y., Willis, R.J.: An iterative scheduling technique for resource-constrained project scheduling. European Journal of Operational Research 56, 370–379 (1992)

    Article  MATH  Google Scholar 

  22. Merkle, D., Middendorf, M., Schmeck, H.: Ant colony optimization for resource constrained project scheduling. IEEE Transaction on Evolutionary Computation 6(4), 333–346 (2002)

    Article  MATH  Google Scholar 

  23. Nonobe, K., Ibaraki, T.: Formulation and tabu search algorithm for the resource constrained project scheduling problem (RCPSP). In: Ribeiro, C.C., Hansen, P. (eds.) Essays and Surveys in Meta-heuristics, pp. 557–588. Kluwer Academic Publishers, Dordrecht (2002)

    Chapter  Google Scholar 

  24. Schirmer, A.: Case-based reasoning and improved adaptive search for project scheduling. Naval Research Logistics 47, 201–222 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  25. Sprecher, A.: Scheduling resource-constrained projects competitively at modest resource requirements. Management Science 46, 710–723 (2000)

    Article  MATH  Google Scholar 

  26. Tormos, P., Lova, A.: A competitive heuristic solution technique for resource-constrained project scheduling. Annals of Operations Research 102, 65–81 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  27. Tormos, P., Lova, A.: An efficient multi-pass heuristic for project scheduling with constrained resources. International Journal of Production Research 41, 1071–1086 (2003)

    Article  MATH  Google Scholar 

  28. Tormos, P., and Lova, A.: Integrating heuristics for resource constrained project scheduling: One step forward, Technical report, Department of Statistics and Operations Research, Universidad Politécnica de Valencia (2003)

    Google Scholar 

  29. Valls, V., Quintanilla, S., Ballestin, F.: Resource-constrained project scheduling: a critical activity reordering heuristic. European Journal of Operational Research 149, 282–301 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  30. Valls, V., Ballestin, F., Quintanilla, S.: A population-based approach to the resource-constrained project scheduling problem. Annals of Operations Research 131, 305–324 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  31. Valls, V., Ballestin, F., Quintanilla, S.: A hybrid genetic algorithm for the Resource-constrained project scheduling problem with the peak crossover operator. Eighth International Workshop on Project Management and Scheduling, 368–371 (2002)

    Google Scholar 

  32. Valls, V., Ballestin, F.: Quintanilla, S.: Justification and RCPSP: A technique that pays, European Journal of Operational Research (forthcoming)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Faculty of Economics and Business Administration, Ghent University, Hoveniersberg 24, Ghent, 9000, Belgium

    Dieter Debels & Mario Vanhoucke

  2. Vlerick Leuven Gent Management School, Operations & Technology Management Centre, Reep 1, Ghent, 9000, Belgium

    Mario Vanhoucke

Authors
  1. Dieter Debels
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  2. Mario Vanhoucke
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Editor information

Editors and Affiliations

  1. INRIA Lille - Nord Europe Research Centre, Parc Scientifique de la Haute Borne, 59650, Villeneuve d’Ascq, France

    El-Ghazali Talbi

  2. UMR-CNRS 6632, Université de Provence, 39 rue F. Joliot-Curie, 13453, Marseille cedex 13, France

    Pierre Liardet

  3. Université Louis Pasteur, LSIIT, FDBT, Pôle API, F-67400, Illkirch, France

    Pierre Collet

  4. INRIA Saclay - Ile-de-France, Parc Orsay Université, 4, rue Jacques Monod, 91893, ORSAY Cedex, France

    Evelyne Lutton

  5. TAO, INRIA Saclay & LRI (UMR CNRS 8623), Bât 490, Université Paris-Sud, 91405, Orsay Cedex, France

    Marc Schoenauer

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© 2006 Springer-Verlag Berlin Heidelberg

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Debels, D., Vanhoucke, M. (2006). The Electromagnetism Meta-heuristic Applied to the Resource-Constrained Project Scheduling Problem. In: Talbi, EG., Liardet, P., Collet, P., Lutton, E., Schoenauer, M. (eds) Artificial Evolution. EA 2005. Lecture Notes in Computer Science, vol 3871. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11740698_23

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  • DOI: https://doi.org/10.1007/11740698_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33589-4

  • Online ISBN: 978-3-540-33590-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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