CLC number: TP18
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
Cited: 12
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CHEN Min-rong, LU Yong-zai, YANG Gen-ke. Multiobjective extremal optimization with applications to engineering design[J]. Journal of Zhejiang University Science A, 2007, 8(12): 1905-1911.
@article{title="Multiobjective extremal optimization with applications to engineering design",
author="CHEN Min-rong, LU Yong-zai, YANG Gen-ke",
journal="Journal of Zhejiang University Science A",
volume="8",
number="12",
pages="1905-1911",
year="2007",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2007.A1905"
}
%0 Journal Article
%T Multiobjective extremal optimization with applications to engineering design
%A CHEN Min-rong
%A LU Yong-zai
%A YANG Gen-ke
%J Journal of Zhejiang University SCIENCE A
%V 8
%N 12
%P 1905-1911
%@ 1673-565X
%D 2007
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2007.A1905
TY - JOUR
T1 - Multiobjective extremal optimization with applications to engineering design
A1 - CHEN Min-rong
A1 - LU Yong-zai
A1 - YANG Gen-ke
J0 - Journal of Zhejiang University Science A
VL - 8
IS - 12
SP - 1905
EP - 1911
%@ 1673-565X
Y1 - 2007
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2007.A1905
Abstract: In this paper, we extend a novel unconstrained multiobjective optimization algorithm, so-called multiobjective extremal optimization (MOEO), to solve the constrained multiobjective optimization problems (MOPs). The proposed approach is validated by three constrained benchmark problems and successfully applied to handling three multiobjective engineering design problems reported in literature. Simulation results indicate that the proposed approach is highly competitive with three state-of-the-art multiobjective evolutionary algorithms, i.e., NSGA-II, SPEA2 and PAES. Thus MOEO can be considered a good alternative to solve constrained multiobjective optimization problems.
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