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Solving the Travelling Salesman Problem using the Kohonen Network Incorporating Explicit Statistics

  • B. John Oommen
  • Necati Aras
  • İ. Kuban Altmel
Conference paper
Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)

Abstract

In this paper we introduce a new self-organizing neural network, the Kohonen Network Incorporating Explicit Statistics (KNIES) that is based on Kohonen’s Self-Organizing Map (SOM). The primary difference between the SOM and the KNIES is the fact that every iteration in the training phase includes two distinct modules — the attracting module and the dispersing module. As a result of the newly introduced dispersing module the neurons maintain the overall statistical properties of the data points. Thus, although in SOM the neurons individually find their places both statistically and topologically, in KNIES they collectively maintain their mean to be the mean of the data points which they represent. The new scheme has been used to solve the Travelling Salesman Problem (TSP). Experimental results for problems taken from TSPLIB [13] indicate that it is a very accurate NN strategy for the TSP — probably the most accurate neural solutions available in the literature.

Keywords

Travelling Salesman Problem Travel Salesman Problem Winner Neuron Activation Bubble Transient Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 1999

Authors and Affiliations

  • B. John Oommen
    • 1
  • Necati Aras
    • 2
  • İ. Kuban Altmel
    • 3
  1. 1.School of Comp. ScienceCarleton UniversityOttawaCanada
  2. 2.Türk Elektrik End. A. Ş. TopkapıİstanbulTürkiye
  3. 3.Dept. of Industrial Eng.Boğaziçi UniversityİstanbulTürkiye

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