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Journal of Zhejiang University SCIENCE C 2010 Vol.11 No.7 P.538-543


Multi-objective differential evolution with diversity enhancement

Author(s):  Bo-yang Qu, Ponnuthurai-Nagaratnam Suganthan

Affiliation(s):  School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, Singapore

Corresponding email(s):   E070088@ntu.edu.sg, epnsugan@ntu.edu.sg

Key Words:  Multi-objective evolutionary algorithm (MOEA), Multi-objective differential evolution (MODE), Diversity enhancement

Bo-yang Qu, Ponnuthurai-Nagaratnam Suganthan. Multi-objective differential evolution with diversity enhancement[J]. Journal of Zhejiang University Science C, 2010, 11(7): 538-543.

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publisher="Zhejiang University Press & Springer",

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%A Ponnuthurai-Nagaratnam Suganthan
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%DOI 10.1631/jzus.C0910481

T1 - Multi-objective differential evolution with diversity enhancement
A1 - Bo-yang Qu
A1 - Ponnuthurai-Nagaratnam Suganthan
J0 - Journal of Zhejiang University Science C
VL - 11
IS - 7
SP - 538
EP - 543
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C0910481

multi-objective differential evolution (MODE) is a powerful and efficient population-based stochastic search technique for solving multi-objective optimization problems in many scientific and engineering fields. However, premature convergence is the major drawback of MODE, especially when there are numerous local Pareto optimal solutions. To overcome this problem, we propose a MODE with a diversity enhancement (MODE-DE) mechanism to prevent the algorithm becoming trapped in a locally optimal Pareto front. The proposed algorithm combines the current population with a number of randomly generated parameter vectors to increase the diversity of the differential vectors and thereby the diversity of the newly generated offspring. The performance of the MODE-DE algorithm was evaluated on a set of 19 benchmark problem codes available from http://www3.ntu.edu.sg/home/epnsugan/. With the proposed method, the performances were either better than or equal to those of the MODE without the diversity enhancement.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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