A Novel Crossover Operator for Genetic Algorithms: Ring Crossover
Abstract
The genetic algorithm (GA) is an optimization and search technique based on the principles of genetics and natural selection. A GA allows a population composed of many individuals to evolve under specified selection rules to a state that maximizes the "fitness" function. In that process, crossover operator plays an important role. To comprehend the GAs as a whole, it is necessary to understand the role of a crossover operator. Today, there are a number of different crossover operators that can be used in GAs. However, how to decide what operator to use for solving a problem? A number of test functions with various levels of difficulty has been selected as a test polygon for determine the performance of crossover operators. In this paper, a novel crossover operator called 'ring crossover' is proposed. In order to evaluate the efficiency and feasibility of the proposed operator, a comparison between the results of this study and results of different crossover operators used in GAs is made through a number of test functions with various levels of difficulty. Results of this study clearly show significant differences between the proposed operator and the other crossover operators.
Keywords
Cite
@article{arxiv.1105.0355,
title = {A Novel Crossover Operator for Genetic Algorithms: Ring Crossover},
author = {Yılmaz Kaya and Murat Uyar and Ramazan Tek\D{j}n},
journal= {arXiv preprint arXiv:1105.0355},
year = {2016}
}
Comments
5 pages, 3 fgigures