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Conference of the Canadian Society for Computational Studies of Intelligence

Canadian AI 2001: Advances in Artificial Intelligence pp 307–316Cite as

Solving the Traveling Salesman Problem Using the Enhanced Genetic Algorithm

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2056))

Abstract

An extension to the Enhanced Genetic Algorithm (EGA) analysis of Gary W. Grewal, Thomas C. Wilson, and Deborah A. Stacey [1] is introduced and applied to the TSP. Previously the EGA had successfully handled constraint-Satisfaction problems, such as graph coloring. This paper broadens the application of the EGA to the specific NP-hard problem, the Traveling Salesman Problem (TSP). The first part of this paper deals with the unique features of the EGA such as running in an unsupervised mode, as applied to the TSP. In the second part, we present and analyze results obtained by testing the EGA approach on three TSP benchmarks while comparing the performance with other approaches using genetic algorithms. Our results show that the EGA approach is novel and successful, and its general features make it easy to integrate with other optimization techniques.

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References

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Author information

Authors and Affiliations

  1. Department of Computing and Information Science, University of Guelph, Guelph, Ontario, Canada, N1G 2W1

    Lixin Yang & Deborah A. Stacey

Authors
  1. Lixin Yang
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  2. Deborah A. Stacey
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Alberta, Edmonton, AB, Canada, T6G 2E8

    Eleni Stroulia

  2. School of Information Technology and Engineering, University of Ottawa, Ottawa, ON, Canada, K1N 6N5

    Stan Matwin

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© 2001 Springer-Verlag Berlin Heidelberg

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Yang, L., Stacey, D.A. (2001). Solving the Traveling Salesman Problem Using the Enhanced Genetic Algorithm. In: Stroulia, E., Matwin, S. (eds) Advances in Artificial Intelligence. Canadian AI 2001. Lecture Notes in Computer Science(), vol 2056. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45153-6_30

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  • DOI: https://doi.org/10.1007/3-540-45153-6_30

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42144-3

  • Online ISBN: 978-3-540-45153-2

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