Evolutionary robustness analysis for multi-objective optimization: Benchmark problems

This paper presents a new approach to robustness analysis in multi-objective optimization problems aimed at obtaining the most robust Pareto front solutions and distributing the solutions along the most robust regions of the optimal Pareto set. A new set of test problems accounting for the different types of robustness cases is presented in this study. Non-dominated solutions are classified according to their degree of robustness and are distributed along the Pareto front according to specific algorithm parameter values. Verification of the proposed method is carried out using the developed test problems and artificial and real world benchmark test problems present in the literature.This work was partially supported by the Portuguese Foundation for Science and Technology under grant PEst-C/CTM/LA0025/2011 (Strategic Project - LA 25 - 2011-2012 and by the Spanish Ministerio de Ciencia e Innovación, under the project Gestión de movilidad efficiente y sostenible, MOVES with grant reference TIN2011-28336