New penalty function with differential evolution for constrained optimization

Abstract

The penalty function is one of the most commonly used approaches for constrained optimization problems. However, it often leads to additional parameters and the parameters are not easy for the users to select. A new way without additional parameters to deal the constrained optimizations was proposed. Firstly, a new penalty function was defined using the constrained functions without additional parameters. Secondly, combining the penalty function and the original objective function, a new objective function without any constrained conditions was got. Then differential evolution algorithm was used to solve the non-constrained optimization problem. The numerical experiments show its advantage over the other existing method.