ε Constrained Differential Evolution Algorithm with a Novel Local Search Operator for Constrained Optimization Problems

Many practical problems can be classified into constrained optimization problems (COPs). epsilon constrained differential evolution (epsilon DE) algorithm is an effective method in dealing with the COPs. In this paper, e constrained differential evolution algorithm with a novel local search operator(epsilon DE-LS) is proposed by utilizing the information of the feasible individuals. In this way, we can guide the infeasible individuals to move into the feasible region more effectively. The performance of the proposed epsilon DE-LS is evaluated by the 22 benchmark test functions. The experimental results empirically show that epsilon DE-LS is highly competitive comparing with some other state-of-the-art approaches in constrained optimization problems.