Parallel Genetic Algorithm using Fuzzy Logic


The KIPS Transactions:PartA, Vol. 13, No. 1, pp. 53-56, Feb. 2006
10.3745/KIPSTA.2006.13.1.53,   PDF Download:

Abstract

Genetic algorithms(GA), which are based on the idea of natural selection and natural genetics, have proven successful in solving difficult problems that are not easily solved through conventional methods. The classical GA has the problem to spend much time when population is large. Parallel genetic algorithm(PGA) is an extension of the classical GA. The important aspect in PGA is migration and GA operation. This paper presents PGAs that use fuzzy logic. Experimental results show that the proposed methods exhibit good performance compared to the classical method.


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Cite this article
[IEEE Style]
Y. H. An and K. H. Kwon, "Parallel Genetic Algorithm using Fuzzy Logic," The KIPS Transactions:PartA, vol. 13, no. 1, pp. 53-56, 2006. DOI: 10.3745/KIPSTA.2006.13.1.53.

[ACM Style]
Young Hwa An and Key Ho Kwon. 2006. Parallel Genetic Algorithm using Fuzzy Logic. The KIPS Transactions:PartA, 13, 1, (2006), 53-56. DOI: 10.3745/KIPSTA.2006.13.1.53.