Publication Type : Journal Article
Publisher : Lecture Notes in Computer Science
Source : Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume 6466 LNCS, Chennai, p.344-350 (2010)
Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-78650892272&partnerID=40&md5=f60c248bee12b9f75400b34bd85fdb25
ISBN : 3642175627; 9783642175626
Keywords : Analysis of means, Benchmark functions, Design, Design factors, Gap model, Genetic algorithms, Lakes, Mathematical models, Optimal combination, Parameter estimation, Parametric study, Performance efficacy, Population sizes, Population statistics, Simplex Crossover, Taguchi, Taguchi methods
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2010
Abstract : In this paper, a parametric study of Generalized Generation Gap (G3) Genetic Algorithm (GA) model with Simplex crossover (SPX) using Taguchi method has been presented. Population size, number of parents and offspring pool size are considered as design factors with five levels. The analysis of mean factor is conducted to find the influence of design factors and their optimal combination for six benchmark functions. The experimental results suggest more experiments on granularity of design factor levels for better performance efficacy. © 2010 Springer-Verlag.
Cite this Research Publication : Dr. Thangavelu S. and Dr. Shunmuga Velayutham C., “Taguchi method based parametric study of generalized generation gap genetic algorithm model”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6466 LNCS, pp. 344-350, 2010.