1998 Volume 11 Issue 11 Pages 600-607
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.
