On an evolutionary approach for constrained optimization problem solving

► Firstly, we examine different variants of differential evolution for solving COPs. ► We then develop and analyze a self-adaptive multi-operator DE algorithm to solve COPs. ► For a faster convergence, we propose a memetic self-adaptive multi-operator DE to solve COPs. ► The algorithm is successfully tested on another set of test problems. ► The algorithm saves 73% of the computational time in comparison to a standard DE.