Regularity Model for Noisy Multiobjective Optimization

Handing Wang; Qingfu Zhang; Licheng Jiao; Xin Yao

doi:10.1109/TCYB.2015.2459137

Regularity Model for Noisy Multiobjective Optimization

Handing Wang, Qingfu Zhang, Licheng Jiao, Xin Yao

Computer Science

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Abstract

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.

Original language	English
Number of pages	13
Journal	IEEE Transactions on Cybernetics
Issue number	99
DOIs	https://doi.org/10.1109/TCYB.2015.2459137
Publication status	E-pub ahead of print - 3 Aug 2015

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title = "Regularity Model for Noisy Multiobjective Optimization",

abstract = "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 existingmultiobjective 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 onsome noisy-free problems.",

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AU - Jiao, Licheng

AU - Yao, Xin

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Y1 - 2015/8/3

N2 - 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 existingmultiobjective 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 onsome noisy-free problems.

AB - 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 existingmultiobjective 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 onsome noisy-free problems.

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Regularity Model for Noisy Multiobjective Optimization

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