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An Enhanced Ant Colony System for the Sequential Ordering Problem

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Operations Research Proceedings 2011

Part of the book series: Operations Research Proceedings ((ORP))

Abstract

A well-known Ant Colony System algorithm for the Sequential Ordering Problem is studied to identify its drawbacks. Some criticalities are identified, and an Enhanced Ant Colony System method that tries to overcome them, is proposed. Experimental results show that the enhanced method clearly outperforms the original algorithm and becomes a reference method for the problem under investigation.

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References

  1. D. Anghinolfi, R. Montemanni, M. Paolucci, and L.M. Gambardella. A hybrid particle swarm optimization approach for the sequential ordering problem. Computers and Operations Research, 38(7):1076–1085, 2011.

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  2. M. Dorigo, V. Maniezzo, and A. Colorni. The Ant System: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, 26(1):29–41, 1996.

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  3. L.M. Gambardella and M. Dorigo. An ant colony system hybridized with a new local search for the sequential ordering problem. INFORMS Journal on Computing, 12(3):237–255, 2000.

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  4. R.Montemanni, D.H. Smith, and L.M. Gambardella. A heuristic manipulation technique for the sequential ordering problem. Computers and Operations Research, 35(12):3931–3944, 2008.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Istituto Dalle Molle di Studi sull’Intelligenza Artificiale, Galleria 2, CH-6928, Manno, Switzerland

    L. M. Gambardella, R. Montemanni & D. Weyland

Authors
  1. L. M. Gambardella
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  2. R. Montemanni
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  3. D. Weyland
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Corresponding author

Correspondence to L. M. Gambardella .

Editor information

Editors and Affiliations

  1. Institut für, Betriebswirtschaftslehre, Universität Zürich, Moussonstrasse, Zurich, 8044, Switzerland

    Diethard Klatte

  2. Inst. Operations Research, ETH Zürich, Rämistr. 101, Zürich, 8092, Switzerland

    Hans-Jakob Lüthi

  3. Institut für, Betriebswirtschaftslehre, Universität Zürich, Moussonstrasse 15, Zurich, 8044, Switzerland

    Karl Schmedders

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© 2012 Springer-Verlag Berlin Heidelberg

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Gambardella, L.M., Montemanni, R., Weyland, D. (2012). An Enhanced Ant Colony System for the Sequential Ordering Problem. In: Klatte, D., Lüthi, HJ., Schmedders, K. (eds) Operations Research Proceedings 2011. Operations Research Proceedings. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29210-1_57

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