Performance assessment of multiobjective optimizers: an analysis and review

E. Zitzler, L. Thiele, M. Laumanns, C.M. Fonseca, V.G. da Fonseca
2003 IEEE Transactions on Evolutionary Computation  
An important issue in multiobjective optimization is the quantitative comparison of the performance of different algorithms. In the case of multiobjective evolutionary algorithms, the outcome is usually an approximation of the Pareto-optimal set, which is denoted as an approximation set, and therefore the question arises of how to evaluate the quality of approximation sets. Most popular are methods that assign each approximation set a vector of real numbers that reflect different aspects of the
more » ... quality. Sometimes, pairs of approximation sets are considered too. In this study, we provide a rigorous analysis of the limitations underlying this type of quality assessment. To this end, a mathematical framework is developed which allows to classify and discuss existing techniques. Index Terms-Evolutionary algorithms, multiobjective optimization, performance assessment, quality indicator.
doi:10.1109/tevc.2003.810758 fatcat:4nfee4wwlnbvxbydgdtl7uug3y