Real-valued constraint optimization with ICHEA

Abstract

Intelligent constraint handling evolutionary algorithm (ICHEA) is a recently proposed variation of evolutionary algorithm (EA) that solves realvalued constraint satisfaction problems (CSPs) efficiently [20]. ICHEA has ability to extract and exploit information from constraints that guides its evolutionary search operators in contrast to traditional EAs that are 'blind' to constraints. Even its efficacy to solve CSPs it was not implemented to handle constraint optimization problems (COPs). This paper proposes an enhancement to ICHEA to solve real-valued COPs. The presented approach demonstrates very competitive results with other state-of-the-art approaches in terms of quality of solutions on well-known benchmark test problems. © 2012 Springer-Verlag.