A new evolutionary algorithm for constrained optimization problems

To solve single-objective constrained optimization problems, a new population-based evolutionary algorithm with elite strategy (PEAES) is proposed with the concept of single and multi-objective optimization. Constrained functions are combined to be an objective function. During the evolutionary process, the current optimal solution is found and treated as the reference point to divide the population into three sub-populations: one feasible and two infeasible ones. Different evolutionary operations of single or multi-objective optimization are respectively performed in each sub-population with elite strategy. Thirteen famous benchmark functions are selected to evaluate the performance of PEAES in comparison of other three optimization methods. The results show the proposed method is valid in efficiency, precision and probability for solving single-objective constrained optimization problems.