A Survey of Performance Assessment for Multiobjective Optimizers

Various randomized search heuristics have been proposed for multiobjective optimization problems. We need evaluate and compare the performance of these optimizers in order to make good use of them. This paper reviews the theory and methods proposed in the past decade and summarize their characteristics based on relevant literature. However, we didn´t list and analyze many methods proposed before because the relevant literature has done it. We look at them from the classification perspective. These assessment methods are classified as quality indicator based approaches and statistic test approach here. For quality indicators, we further classify them Pareto dominance compliant and non-compliant, unary and binary parameters. This enables us to choose suitable assessment measures in practice.