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An Ant Colony Optimization and Bayesian Network Structure Application for the Asymmetric Traveling Salesman Problem

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 7198)

Abstract

The asymmetric traveling salesman problem (ATSP) is an NP-hard problem. The Bayesian network structure which describes conditional independence among subsets of variables is useful in reasoning uncertainty. The ATSP is formed as the Bayesian network structure and solved by the ant colony optimization (ACO) in this study. The proposed algorithm is tested in different sample size. The exam case is finding customer preference’s city sequence. Results show the proposed algorithm has a higher joint probability than random selected case. More applications such as the sequential decision, the variable ordering or the route planning can also implement.

Keywords

  • Ant colony optimization
  • Bayesian network
  • Asymmetric Traveling Salesman Problem

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© 2012 Springer-Verlag Berlin Heidelberg

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Chen, NH. (2012). An Ant Colony Optimization and Bayesian Network Structure Application for the Asymmetric Traveling Salesman Problem. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Intelligent Information and Database Systems. ACIIDS 2012. Lecture Notes in Computer Science(), vol 7198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28493-9_9

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  • DOI: https://doi.org/10.1007/978-3-642-28493-9_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28492-2

  • Online ISBN: 978-3-642-28493-9

  • eBook Packages: Computer ScienceComputer Science (R0)