An efficient genetic algorithm with fuzzy c-means clustering for traveling salesman problem

Jong Won Yoon, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Genetic algorithms (GA) are one of effective approaches to solve the traveling salesman problem (TSP). When applying GA to the TSP, it is necessary to use a large number of individuals in order to increase the chance of finding optimal solutions. However, this incurs high evaluation costs which make it difficult to obtain fitness values of all the individuals. To overcome this limitation we propose an efficient genetic algorithm based on fuzzy clustering which reduces evaluation costs with minimizing loss of performance. It works by evaluating only one representative individual for each cluster of a given population, and estimating the fitness values of the others from the representatives indirectly. A fuzzy c-means algorithm is used for grouping the individuals and the fitness of each individual is estimated according to membership values. The experiments were conducted with randomly generated cities, and the performance of the method was evaluated by comparing to other GAs. The results showed the usefulness of the proposed method on the TSP.

Original languageEnglish
Title of host publication2011 IEEE Congress of Evolutionary Computation, CEC 2011
Pages1452-1456
Number of pages5
DOIs
Publication statusPublished - 2011 Aug 29
Event2011 IEEE Congress of Evolutionary Computation, CEC 2011 - New Orleans, LA, United States
Duration: 2011 Jun 52011 Jun 8

Publication series

Name2011 IEEE Congress of Evolutionary Computation, CEC 2011

Other

Other2011 IEEE Congress of Evolutionary Computation, CEC 2011
CountryUnited States
CityNew Orleans, LA
Period11/6/511/6/8

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Theoretical Computer Science

Fingerprint Dive into the research topics of 'An efficient genetic algorithm with fuzzy c-means clustering for traveling salesman problem'. Together they form a unique fingerprint.

  • Cite this

    Yoon, J. W., & Cho, S. B. (2011). An efficient genetic algorithm with fuzzy c-means clustering for traveling salesman problem. In 2011 IEEE Congress of Evolutionary Computation, CEC 2011 (pp. 1452-1456). [5949786] (2011 IEEE Congress of Evolutionary Computation, CEC 2011). https://doi.org/10.1109/CEC.2011.5949786