Constrained Multiobjective Optimization by Evolutionary Algorithms


An evolutionary computation technique for constrained multiobjective optimization problems is proposed in this paper. A Nondominated Sorting Evolutionary Algorithm is used to find a number of nondominated solutions to the problem. Then the decision maker can choose the most appropriate solution according to the current situation. The proposed technique to handle constraints is not dependent on the problem. Ranking selection and a crowding factor model based niche formation technique is used to maintain diversity in the population. Simulation results show a good performance of the technique. Keywords: Evolutionary Algorithm; constrained multiobjective optimization; Nondominated Sorting.