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Taguchi Method Based Parametric Study of Generalized Generation Gap Genetic Algorithm Model

机译:基于Taguchi方法的广义发电间隙遗传算法模型参数研究

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摘要

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.
机译:本文利用Taguchi方法对具有单工交叉(SPX)的广义生成间隙(G3)遗传算法(GA)模型进行了参数研究。人口规模,父母数量和后代池规模被认为是具有五个层次的设计因素。进行均值因子分析,以找出设计因子及其对六个基准函数的最佳组合的影响。实验结果表明,对设计因子水平的粒度进行了更多的实验,以获得更好的性能。

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