A benchmark for quality indicators in multi-objective optimization.

  • Authors:
  • Giovanni Lizarraga;Arturo Hernandez;Salvador Botello

  • Affiliations:
  • CIMAT, Guanajuato, Mexico;CIMAT, Guanajuato, Mexico;CIMAT, Guanajuato, Mexico

  • Venue:
  • Proceedings of the 11th Annual conference on Genetic and evolutionary computation
  • Year:
  • 2009

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Abstract

Comparing the performance of different evolutive Multi-Objective algorithms is an open problem. With time, many performance measures have been proposed. Unfortunately, the evaluations of many of these performance measures disagree with the common sense of when a non-dominated set is better than another. In this work we present a benchmark that is helpful to check if a performance measure actually has a good behavior. Some of the most popular performance measures in literature are tested. The results are valuable for a better understanding of what performance measures are better.