Performance Analysis of Clustering Based Genetic Algorithm
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Date
2016-07-26
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
In this work, performance analysis of Clustering based Genetic Algorithm (CGA)
proposed in the literature has been undertaken. The proposed CGA on which the
performance analysis of this paper is based involve the use of two centroids based
clustering technique as a new method of chromosomes selection at the reproduction
stage in a typical Genetic Algorithm. Population Control and Polygamy mating techniques
were introduced to improve the performance of the algorithm. Results obtained from the
determination of optimal solutions to the: Sphere, Schwefel 2.4, Beale and another known
optimization functions carried out in this work shows that the proposed CGA converges
to global solutions within few iterations and can also be adopted for function optimization
aside from the route optimization problem previously reported in Literature.
Description
Keywords
Sociology, Statistics, Genetic algorithms, Biological cells, Optimization, Algorithm design and analysis, Wheels Clustering, Evolutionary Algorithm, Function Optimization
Citation
Najeeb, A. R., Aibinu, A. M., Nwohu, M. N., Salami, M. J. E., & Salau, H. B. (2016, July). Performance analysis of clustering based genetic algorithm. In 2016 International Conference on Computer and Communication Engineering (ICCCE) (pp. 327-331). IEEE.