Spread Assessment for Evolutionary Multi-Objective Optimization


Abstract

Convergence, uniformity and spread are three basic issues in comparing the performance of multi-objective evolutionary algorithms. However, most of metrics pay more attention on former two performance indices. In this paper, we introduce a metric for evaluating the spread of non-dominated solutions. Unlike existed metrics only calculating the extreme solutions in objective space, this metric defines boundary concept of non-dominated set. And it evaluates the extent of boundary solutions by projecting them on low-dimensional spaces. Moreover, the centroid of solutions set is introduced to avoid the impact of different convergence result of algorithms. From a comparative study on several test problems, the metric is examined to assess spread of non-dominated solutions set in objective space.