Coevolution Evolutionary Algorithm: A Survey

Abstract

Evolutionary Computing techniques have become one of the most powerful tools for solving optimization problems and is
based on the mechanisms of natural selection and genetics. In Evolutionary Algorithm, Co-evolution is a natural choice for learning in problem
domains where one agent’s behaviour is directly related to the behaviour of other agents. Co-evolution provides a framework to implement
search heuristics that are more elaborate than those driving the exploration of the state space in canonical evolutionary systems. This paper
presents the concept of Co-evolutionary learning and explains a search procedure which successfully addresses the underlying impediments in
Co-evolutionary search. Co-evolution employs evolutionary algorithms to solve a high-dimensional search problem by decomposing it into lowdimensional
subcomponents. The objective of this survey is to discuss about the various existing Co-evolutionary algorithm and their successful
implementation in real world optimization problem. Hence the outcome of the study is to bring out the various research opportunities in
implementing the concept of Co-evolution for many optimization problems in different application

Keywords: Evolutionary Computation, Evolutionary Algorithm, Co-evolution Computation and Co-evolutionary Algorithm.