A Post-Pareto Approach for Multi-Objective Decision Making Using a Non-Uniform Weight Generator Method

There exist two general approaches to solve multiple objective problems. The first approach involves the aggregation of all the objective functions into a single composite objective function. Mathematical methods such as the weighted sum method, goal programming, or utility functions are methods that pertain to this general approach. The output of this method is a single solution. On the other hand, we have the multiple objective evolutionary algorithms that offer the decision maker a set of trade off solutions usually called non dominated solutions or, Pareto-optimal solutions. This set is usually very large and the decision maker faces the problem of reducing the size of this set to have a manageable number of solutions to analyze. This paper presents a post- Pareto approach to prune the non-dominated set of solutions obtained by multiple objective evolutionary algorithms. The proposed approach uses a non-uniform weight generator method to reduce the size of the Pareto-optimal set. A pair of examples is presented to show the performance of the method.