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A benchmark for quality indicators in multi-objective optimization.

Published:08 July 2009Publication History

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.

References

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  4. ]]G. Lizárraga, A. Hernández, and S. Botello. A set of test cases for performance measures in multi-objective optimization. In MICAI 2008: Advances in Artificial Intelligence, pages 429--439. Springer Berlin / Heidelberg, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
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    • Published in

      cover image ACM Conferences
      GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation
      July 2009
      2036 pages
      ISBN:9781605583259
      DOI:10.1145/1569901

      Copyright © 2009 Copyright is held by the author/owner(s)

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 8 July 2009

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