Comparison Study for Clonal Selection Algorithm and Genetic Algorithm
Neural and Evolutionary Computing
2012-09-14 v1
Abstract
Two metaheuristic algorithms namely Artificial Immune Systems (AIS) and Genetic Algorithms are classified as computational systems inspired by theoretical immunology and genetics mechanisms. In this work we examine the comparative performances of two algorithms. A special selection algorithm, Clonal Selection Algorithm (CLONALG), which is a subset of Artificial Immune Systems, and Genetic Algorithms are tested with certain benchmark functions. It is shown that depending on type of a function Clonal Selection Algorithm and Genetic Algorithm have better performance over each other.
Keywords
Cite
@article{arxiv.1209.2717,
title = {Comparison Study for Clonal Selection Algorithm and Genetic Algorithm},
author = {Ezgi Deniz Ulker and Sadik Ulker},
journal= {arXiv preprint arXiv:1209.2717},
year = {2012}
}
Comments
12 pages, 12 figures, 2 tables