GA-based multi-objective optimization

In this paper, we propose a hybrid algorithm for finding a set of multi-solutions of multi-objective optimization problems. In the proposed algorithm, GB is adopted to solve the multi-modal function optimization, a local search procedure is applied to each solution generated by genetic operations. The trim of the proposed algorithm is not only to determine the global optimal solution, but also to try to find all the nondominated solutions of a multi-objective optimization problem. The choice of the final solution set is left to the decision maker's preference. nigh search ability of the proposed algorithm is demonstrated by computer simulation.