Differential Evolution with a Constraint Consensus Mutation for Solving Optimization Problems

in the literature, a considerable number of mutation operators have been proposed, which are the key search operators in differential evolution algorithm for solving optimization problems. Although those operators were developed in the context of unconstrained optimization, they were widely used in constrained optimization. However, those operators did not contain any mechanism that would reduce the constraint violation in the search process. Therefore, in this paper, a new mutation operator based on the constraint consensus method is proposed, which can help infeasible points reach the feasible region quickly. The algorithm is tested on the CEC2010 constrained benchmark problems. The experimental results show that the proposed algorithm is able to obtain better solutions in comparison with the state-of-the-art algorithms.