Optimization via evolutionary processes

Abstract

Evolutionary processes have attracted considerable interest in recent years for solving a variety of optimization problems. This article presents a synthesizing overview of the underlying concepts behind evolutionary algorithms, a brief review of genetic algorithms, & motivation for hybridizing genetic algorithms with other methods. Operating concepts governing evolutionary strategies & differences between such strategies & genetic algorithms are highlighted. Genetic programming techniques & their application are discussed briefly. To demonstrate the applicability of these principles, representative examples are drawn from different disciplines.