Fuzzy Penalty Function Approach for Constrained Function Optimization with Evolutionary Algorithms

In this paper, a novel fuzzy penalty function approach is proposed for solving the constrained optimization problems using evolutionary algorithms. The fuzzy penalty is constructed according to the information contained in individuals so that it can be tuned to reflect the appropriate penalty need for better search. Simulations on ten case studies indicate that the proposed method is very effective.