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A Biologically Inspired Solution for Fuzzy Travelling Salesman Problem

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Artificial Intelligence and Signal Processing (AISP 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 427))

Abstract

Recently, biologically inspired methods have been proposed for solving combinatorial optimization problems like the travelling salesman problem (TSP). This is a well-known combinatorial optimization problem which belongs to NP-hard class. It is desired to find a minimum-cost tour while visiting each city once. This paper presents a variant of the TSP in which the traveling cost between each pair of cities is represented by fuzzy numbers instead of a deterministic value. To solve this fuzzy TSP, a bio-inspired algorithm based on physarum polycephalum model is used. This organism can find the shortest route through a maze by trying to locate the food sources placed at the exits. It also can attract the maximum amount of nutrients in the shortest possible time. Our algorithm is capable of finding an optimal solution for graphs with both crisp and fuzzy numbers as their cost of edges. Numerical examples of some networks are used to illustrate the efficiency of the proposed method.

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Author information

Authors and Affiliations

  1. Computer Science and Engineering Department, Shiraz University, Shiraz, Iran

    Elham Pezhhan & Eghbal Mansoori

Authors
  1. Elham Pezhhan
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  2. Eghbal Mansoori
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Correspondence to Elham Pezhhan .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Sharif University of Technology, Tehran, Iran

    Ali Movaghar

  2. Department of Computer Engineering, Sharif University of Technology, Tehran, Iran

    Mansour Jamzad

  3. Sharif University of Technology, Tehran, Iran

    Hossein Asadi

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Pezhhan, E., Mansoori, E. (2014). A Biologically Inspired Solution for Fuzzy Travelling Salesman Problem. In: Movaghar, A., Jamzad, M., Asadi, H. (eds) Artificial Intelligence and Signal Processing. AISP 2013. Communications in Computer and Information Science, vol 427. Springer, Cham. https://doi.org/10.1007/978-3-319-10849-0_28

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  • DOI: https://doi.org/10.1007/978-3-319-10849-0_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10848-3

  • Online ISBN: 978-3-319-10849-0

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