A review of techniques for online control of parameters in swarm intelligence and evolutionary computation algorithms

Abstract

The two major groups representing biologically inspired algorithms are swarm intelligence (SI) and evolutionary computation (EC). Both SI and EC share common features such as the use of stochastic components during the optimisation process and various parameters for configuration. The setup of parameters in swarm and in evolutionary algorithms has an important role in defining their behaviour, guiding the search and biasing the quality of final solutions. In addition, an appropriate setting for the parameters may change during the optimisation process making this task even harder. The present work brings an up-to-date discussion focusing on online parameter control strategies applied in SI and EC. Also, this review analyses and points out the key techniques and algorithms used and suggests some directions for future research.