A Set of Test Cases for Performance Measures in Multiobjective Optimization

Authors:
Giovanni Lizárraga;Arturo Hernández;Salvador Botello
Affiliations:
Department of Computer Science, Center for Research in Mathematics (CIMAT),;Department of Computer Science, Center for Research in Mathematics (CIMAT),;Department of Computer Science, Center for Research in Mathematics (CIMAT),
Venue:
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Year:
2008

Citing 3
Cited 1

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Evolutionary Algorithms for Solving Multi-Objective Problems

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Performance assessment of multiobjective optimizers: an analysis and review

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Some convergence-based M-ary cardinal metrics for comparing performances of multi-objective optimizers

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Abstract

Comparing the performance of different evolutive multiobjective 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 multiobjective algorithm is performing 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.