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发布时间：2019-03-11

论文类型：期刊论文

发表时间：2008-09-15

发表刊物：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

收录刊物：Scopus、CPCI-S、EI

卷号：5227 LNAI

页面范围：140-147

ISSN号：3540859837

关键字：Generalized differential evolution; estimation of distribution algorithm; multi-objective optimization

摘要：This paper proposed a multi-objective evolutionary algorithm (called by GDE-EDA hereinafter). The proposed algorithm combined a generalized differential evolution (DE) with an estimation of distribution algorithm (EDA). This combination can simultaneously use global information of population extracted by EDA and differential information by DE. Thus, GDE-EDA can obtain a better distribution of the solutions by EDA while keeping the fast convergence exhibited by DE. The experimental results of the proposed GDE-EDA algorithm were reported on a suit of widely used test functions, and compared with GDE and NSGA-II in the literature. © 2008 Springer-Verlag Berlin Heidelberg.