Evolutionary robustness analysis for multi-objective optimization: Benchmark problems Articles uri icon

authors

  • GASPAR CUNHA, ANTONIO
  • FERREIRA, JOSE
  • RECIO ISASI, GUSTAVO

publication date

  • May 2014

start page

  • 771

end page

  • 793

issue

  • 5

volume

  • 49

International Standard Serial Number (ISSN)

  • 1615-147X

Electronic International Standard Serial Number (EISSN)

  • 1615-1488

abstract

  • 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. © 2013 Springer-Verlag Berlin Heidelberg.

subjects

  • Computer Science

keywords

  • multi-objective optimization; multidisciplinary; robustness; test problems