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Solving Time-Dependent Traveling Salesman Problems Using Ant Colony Optimization Based on Predicted Traffic

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Distributed Computing and Artificial Intelligence

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 151))

Abstract

In this paper, we propose an ant colony optimization based on the predicted traffic for time-dependent traveling salesman problems (TDTSP), where the travel time between cities changes with time. Prediction values required for searching is assumed to be given in advance. We previously proposed a method to improve the search rate of Max-Min Ant System (MMAS) for static TSPs. In the current work, the method is extended so that the predicted travel time can be handled and formalized in detail. We also present a method of generating a TDTSP to use in evaluating the proposed method. Experimental results using benchmark problems with 51 to 318 cities suggested that the proposed method is better than the conventional MMAS in the rate of search.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Ibaraki, Japan

    Hitoshi Kanoh & Junichi Ochiai

Authors
  1. Hitoshi Kanoh
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  2. Junichi Ochiai
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Corresponding author

Correspondence to Hitoshi Kanoh .

Editor information

Editors and Affiliations

  1. Dept. Computer Science &, Intelligent Systems, Osaka Prefecture University, Gakuen-chu 1-1, Sakai, Osaka, 599-8531, Japan

    Sigeru Omatu

  2. , Department of Computing Science, University of Salamanca, Plaza de la Merced S/N, Salamanca, 37008, Spain

    Juan F. De Paz Santana

  3. , Department of Computing Science, University of Salamanca, Plaza de la Merced S/N, Salamanca, 37008, Spain

    Sara Rodríguez González

  4. Escuela Politécnica Superior (EPS), Depto. Informática, Universidad Carlos III de Madrid, Avenida de la Universidad Carloss III 22, Madrid, 28270, Spain

    Jose M. Molina

  5. , Data Processing and Simulation Group, Universidad Politécnica de Madrid, Calle de Ramiro de Maeztu, 7, Madrid, 28040, Spain

    Ana M. Bernardos

  6. Faculty of Science, Department of Computing Science, University of Salamanca, Plaza de la Merced S/N, Salamanca, 37008, Spain

    Juan M. Corchado Rodríguez

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© 2012 Springer-Verlag Berlin Heidelberg

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Kanoh, H., Ochiai, J. (2012). Solving Time-Dependent Traveling Salesman Problems Using Ant Colony Optimization Based on Predicted Traffic. In: Omatu, S., De Paz Santana, J., González, S., Molina, J., Bernardos, A., Rodríguez, J. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent and Soft Computing, vol 151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28765-7_4

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  • DOI: https://doi.org/10.1007/978-3-642-28765-7_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28764-0

  • Online ISBN: 978-3-642-28765-7

  • eBook Packages: EngineeringEngineering (R0)

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