A novel selection operator of cultural algorithm

Abstract

Cultural Algorithms (CAs) are a series of new algorithms which depict cultural evolution as a process of dual inheritance. In this paper, cultural algorithm using Genetic Algorithms (GAs) and the knowledge in belief space to guide the evolution of population space is introduced. GAs simply use the fitness to evaluate the quality of solutions, however, it may lose the diversity of population and even lead to premature convergence. To solve this problem, we put forward a novel selection operator. Compared with conventional CA based on GA, CA with our selection operator performs better in the global convergence. © 2011 Springer-Verlag Berlin Heidelberg.