Genetic Algorithm: A Search of Complex Spaces

Abstract

Living species solve very complex problem of optimization through the mechanism of evolution and natural selection. Genetic Algorithm has been a field of active interest and applied to solve problems almost in all the fields like Computer Science, Electrical Engg., Mechanical Engg., Optimization, Biology and Image Processing etc. One important application of Genetic Algorithm is to search complex spaces and function optimization. A genetic algorithm begins its search with random solution of the problem. The initial population is evolved to new population using Genetic operators like reproduction, crossover and mutation. A Genetic Algorithm keeps evolving the successive populations unless some criterion is met or a reasonable acceptable solution is found. In this paper Genetic Algorithm has been applied to schwefel function to find the best fit chromosome so far.