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Improved Multiple Ant Colonies System for Traveling Salesman Problems

  • Hidenori Kawamura
  • Masahito Yamamoto
  • Azuma Ohuchi
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 43)

Abstract

Recently, many kinds of approximate optimization methods have been proposed. The ant system (AS), which is originally proposed by Dorigo et al, is one such algorithm. To improve the basic performance of the AS algorithm, we developed the AS into a multiple ant colonies system (MACS) by introducing multiple colonies and colony-level interactions. MACS showed better performance compared with ACO [Kawamura (2000)]. In this study, we implemented no special heuristic technique as is often used in approximate optimization methods; therefore, it is necessary to investigate the performance of MACS with some heuristics for further development of MACS. In this paper, we implement 2-opt heuristic to the MACS for more powerful performance for solving TSPs.

Keywords

Ant Colony Optimization Ant System Multi-agent Systems Combinatorial Optimization Problems Traveling Salesman Problems 

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Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Hidenori Kawamura
    • 1
  • Masahito Yamamoto
    • 1
  • Azuma Ohuchi
    • 1
  1. 1.Laboratory of Harmonious Systems Eng., Division of Complex Systems Eng., Institute of System and Information Eng., Graduate School of Eng.Hokkaido UniversitySapporo, HokkaidoJapan

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