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Agent-Based Evolutionary System for Traveling Salesman Problem

  • Rafał Dreżewski
  • Piotr Woźniak
  • Leszek Siwik
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5572)

Abstract

Evolutionary algorithms are heuristic techniques based on Darwinian model of evolutionary processes, which can be used to find approximate solutions of optimization and adaptation problems. Agent-based evolutionary algorithms are a result of merging two paradigms: evolutionary algorithms and multi-agent systems. In this paper agent-based evolutionary algorithm for solving well known Traveling Salesman Problem is presented. In the experimental part, results of experiments comparing agent-based evolutionary algorithm and classical genetic algorithm are presented.

Keywords

Genetic Algorithm Evolutionary Algorithm Travel Salesman Problem Travel Salesman Problem Vehicle Route Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Agent-based evolution platform (jAgE), http://age.iisg.agh.edu.pl
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    Bäck, T., Fogel, D., Michalewicz, Z. (eds.): Handbook of Evolutionary Computation. IOP Publishing/ Oxford University Press (1997)Google Scholar
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    Dreżewski, R.: A model of co-evolution in multi-agent system. In: Mařík, V., Müller, J.P., Pěchouček, M. (eds.) CEEMAS 2003. LNCS, vol. 2691, pp. 314–323. Springer, Heidelberg (2003)CrossRefGoogle Scholar
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    Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. Springer, Heidelberg (1996)CrossRefzbMATHGoogle Scholar
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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Rafał Dreżewski
    • 1
  • Piotr Woźniak
    • 1
  • Leszek Siwik
    • 1
  1. 1.Department of Computer ScienceAGH University of Science and TechnologyKrakówPoland

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