Using a repair genetic algorithm for solving constrained nonlinear optimization problems

Constraint handling is a major concern in using genetic algorithm (GA) to solve constrained optimization problems. In this paper, we use a repair genetic algorithm for solving constrained nonlinear optimization problems. The repair operator is used into a simple GA as a special operator. We present an effective algorithm for solving the repair problem based on nonlinear programming. Experiments using some nonsmooth test problems are presented and compared with the results obtained with the ga function in MATLAB. These results demonstrate the efficiency and robustness of the proposed approach.