Parameter control in Differential Evolution for constrained optimization

In this paper we present the addition of parameter control in a differential evolution algorithm for constrained optimization. Three parameters are self-adapted by encoding them within each individual and a fourth parameter is controlled by a deterministic approach. A set of experiments are performed in order (1) to determine the performance of the modified algorithm with respect to its original version, (2) to analyze the behavior of the self-adaptive parameter values and (3) to compare it with respect to state-of-the-art approaches. Based on the obtained results, some findings regarding the values for the DE parameters as well as for the parameters related with the constraint-handling mechanism are discussed.