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Two-Stage ACO to Solve the Job Shop Scheduling Problem

  • Amilkar Puris
  • Rafael Bello
  • Yaima Trujillo
  • Ann Nowe
  • Yailen Martínez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4756)

Abstract

In this paper, a multilevel approach of Ant Colony Optimization to solve the Job Shop Scheduling Problem (JSSP) is introduced. The basic idea is to split the heuristic search performed by ants into two stages; only the Ant System algorithm belonging to ACO was regarded for the current research. Several JSSP instances were used as input to the new approach in order to measure its performance. Experimental results obtained conclude that the Two-Stage approach significantly reduces the computational time to get a solution similar to the Ant System.

Keywords

Ant Colony Optimization Ant System Job Shop Scheduling Problem 

References

  1. 1.
    Garey, M.R., D.S.: Computers and Intractability, A Guide to the Theory of NP-Completeness. W.H Freeman and Company (1979)Google Scholar
  2. 2.
    Dorigo, M., et al.: The Ant System: Optimization by a colony of cooperating agents. Man and Cybernetics-Part B 26(1), 1–13 (1996)CrossRefGoogle Scholar
  3. 3.
    Dorigo, M., et al.: Ant algorithms for discrete optimization. Artificial Life 5(2), 137–172 (1999)CrossRefGoogle Scholar
  4. 4.
    Dorigo, M., Stutzle, T.: Ant Colony Optimization. MIT Press, Cambridge (2004)zbMATHGoogle Scholar
  5. 5.
    Stutzle, T.: An ant approach for the flow shop problem. In: EUFIT 1998, Verlag Mainz, Aachen, vol. 3, pp. 1560–1564 (1998)Google Scholar
  6. 6.
    Merkle, D., Middendorf, M., Schmeck, H.: Ant Colony Optimization for Resource Constrained Project Scheduling. IEEE Transactions on Evolutionary Computation 6(4), 333–346 (2002)CrossRefGoogle Scholar
  7. 7.
    Merkle, D., Middendorf, M.: Ant Colony Optimization with Global Pheromone Evaluation for Scheduling a Single Machine. Journal of Applied Intelligence 105–111 (2003)Google Scholar
  8. 8.
    Dorigo, M., Gambardella, L.M.: Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem. IEEE Transactions on Evolutionary Computation 1(1), 53–66 (1997)CrossRefGoogle Scholar
  9. 9.
    Bullnheimer, B., Hartl, R.F., Strauss, C.: A New Rank Based Version of the Ant System: A Computational Study. Central European Journal for Operations Research and Economics 7(1), 25–38 (1999)zbMATHMathSciNetGoogle Scholar
  10. 10.
    Gambardella, L.M., Taillard, E., Agazzi, G.: MACS-VRPTW: A Multiple Ant Colony System for Vehicle Routing Problems with Time Window. In: David Corne, Marco Dorigo, and Fred Glover, editors, New Ideas in Optimization, pp. 63–76. McGraw-Hill, London (1999)Google Scholar
  11. 11.
    Blum, C., Sampels, M.: An ant Colony Optimization Algorithm to tackle Shop Scheduling ProblemsGoogle Scholar
  12. 12.
    Colorni, A., Dorigo, M., Maniezzo, V., Trubian, M.: Ant system for Job-shop Scheduling. JORBEL - Belgian Journal of Operations Research, Statistics and Computer Science 34(1), 39–53 (1994)zbMATHGoogle Scholar
  13. 13.
    Blum, C., Sampels, M.: An ant Colony Optimization Algorithm for FOP Shop Scheduling: A case study on different pheromone representations. In: CEC 2002, pp. 1558–1563 (2002)Google Scholar
  14. 14.
    Ventresca, M., Ombuki, B.: Ant Colony Optimization for Job Shop Scheduling Problem. From Proceedings pf Artificial Intelligence and Soft Computing (2004)Google Scholar
  15. 15.
    Dorigo, M., Gambardela, L.M.: Ant colonies for the traveling salesman problem. BioSystems (43), 73–81 (1997)CrossRefGoogle Scholar
  16. 16.
    Dorigo, M., Stützle, T.: ACO Algorithms for the Traveling Salesman Problem. Evolutionary Algorithms in Engineering and Computer Science: Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming, Genetic Programming and Industrial Applications. John Wiley & Sons, Chichester (1999)Google Scholar
  17. 17.
  18. 18.
    Stutzle, T., Hoos, H.: The Max-Min Ant System. Future Generation Computer System 16(8), 889–914 (2000)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Amilkar Puris
    • 1
  • Rafael Bello
    • 1
  • Yaima Trujillo
    • 1
  • Ann Nowe
    • 2
  • Yailen Martínez
    • 1
  1. 1.Department of Computer Science, Universidad Central de Las VillasCuba
  2. 2.CoMo Lab, Department of Computer Science, Vrije Universiteit BrusselBelgium

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