Comparative analysis of Selective Clonal Mutation with conventional GA operators in solar tracking environment

Abstract

Genetic Algorithm (GA) belongs to elementary stochastic optimization algorithms inspired by evolution.It points out the ability of simple representations using bit strings to encode complicated structures and the power of simple transformations to reach the desired solution. Research shows that a new operator namely Selective Clonal Mutation (SCM) for better genetic solutions has been successfully developed so that faster convergence to the best desired solution could be obtained. This operator has produced the best fitness value as compared to the conventional genetic algorithm result within 50 generation, Selective Clonal Mutation (SCM) is able to produce the best fitness value at 0.01731 with optimum voltage 10.05V in solar tracking environment. © (2012) Trans Tech Publications, Switzerland.