A future perspective survey on bio-inspired algorithms based self-organization techniques for GA

Abstract

Genetic algorithms (GAs) are the most important evolutionary computation technique that is used to solve various complex problems that involve a large search space. To have a performance improvement over GA the concept of Hybrid genetic algorithms that were inspired by the biological behavior of different living beings was put to use to solve the NP-completeness problems. In this paper, a survey on the various recent working HGA with bio-inspired algorithms that exhibits self-organization behavior is performed. This paper discusses the various Biological self-organization behaviors and the generalized self-organization behaviors that are used to solve combinatorial optimization problems. This paper helps the scholars and researchers to have a better understanding on the bio-inspired based self-organization techniques for Genetic algorithm so that they can formulate new algorithms based on existing SO techniques.