Regularity Model for Noisy Multiobjective Optimization

Handing WANG, Qingfu ZHANG, Licheng JIAO, Xin YAO

Research output: Journal PublicationsJournal Article (refereed)peer-review

47 Citations (Scopus)


Regularity models have been used in dealing with noise-free multiobjective optimization problems. This paper studies the behavior of a regularity model in noisy environments and argues that it is very suitable for noisy multiobjective optimization. We propose to embed the regularity model in an existing multiobjective evolutionary algorithm for tackling noises. The proposed algorithm works well in terms of both convergence and diversity. In our experimental studies, we have compared several state-of-the-art of algorithms with our proposed algorithm on benchmark problems with different levels of noises. The experimental results showed the effectiveness of the regularity model on noisy problems, but a degenerated performance on some noisy-free problems. © 2013 IEEE.
Original languageEnglish
Article number7175019
Pages (from-to)1997-2009
Number of pages13
JournalIEEE Transactions on Cybernetics
Issue number9
Early online date3 Aug 2015
Publication statusPublished - Sept 2016
Externally publishedYes

Bibliographical note

The work of X. Yao was supported by the Royal Society Wolfson Research Merit Award.


  • Local principal component analysis (PCA)
  • multiobjective optimization
  • noise
  • regularity model


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