パレート分割手法を用いた遺伝的アルゴリズムの多目的最適化問題への適用

抄録

In this paper, a genetic algorithm using a Pareto partitioning method to multiobjective optimization problems is proposed. The purpose of the proposed method is to generate a set of non-dominated solutions that is properly distributed in the neighborhood of the trade-off surface. The genetic search using the proposed method uniformly controls the convergence of non-dominated solutions in the objective space. Simulation results show that the GA using the Pareto partitioning method has good performances better than the traditional GA approaches for several 2-objective function optimization problems and 2-objective flow-shop scheduling problems.