Comparison Study for Clonal Selection Algorithm and Genetic Algorithm
This is an incremental comparison for researchers in metaheuristic optimization, with no broad impact claimed.
The study compared the performance of Clonal Selection Algorithm (CLONALG) and Genetic Algorithms on benchmark functions, finding that each algorithm performs better than the other depending on the function type.
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.