Gray-Coded Clonal Selection Algorithm for Optimization Problem

Abstract

Clonal Selection Algorithm (CSA), inspired by the clonal selection theory, has gained much attention and wide applications. In most common forms, the CSAs use a binary representation of variables, and the emulated immune operators, mutation, proliferation, selection, for example, are made to act on it. However, the binary representation often suffers from the so-called Hamming Cliff problem. In order to overcome this problem, a Gray-coded CSA is presented and used to solve optimization problems. The algorithm is applied to numerous bench-mark problems of numerical optimization problems and the computational results show effectiveness of the proposed algorithm.