Improved multi-objective evolutionary algorithm based on differential evolution

doi:10.3778/j.issn.1002-8331.2008.29.014

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (29): 51-56.DOI: 10.3778/j.issn.1002-8331.2008.29.014

• 理论研究 • Previous Articles Next Articles

Improved multi-objective evolutionary algorithm based on differential evolution

LI Ke,ZHENG Jin-hua

Institute of Information Engineering，Xiangtan University，Xiangtan，Hunan 411105，China

Received:2008-04-11 Revised:2008-07-18 Online:2008-10-11 Published:2008-10-11
Contact: LI Ke

一种改进的基于差分进化的多目标进化算法

李珂,郑金华

湘潭大学信息工程学院，湖南湘潭 411105

通讯作者: 李珂

Abstract

Abstract: Recently，the use of evolutionary algorithms（EAs） to solve the Multi-objective Optimization Problems（MOPs） has attracted much attention.EA is a population based optimized approach which can find a group of Pareto-optimal solutions in a single run.Differential Evolution（DE） is a branch of EA that is developed to handle problems over continuous domains.An improved Multi-objective Evolutionary Algorithm is proposed based on Differential Evolution（CDE） to solve MOPs.The proposed algorithm is compared to the other two classical Multi-objective Evolutionary algorithms（MOEAs） NSGA-II and SPEA2 with the experiment results.

Key words: multi-objective optimization, differential evolution, Multi-objective Optimization（CDE）

摘要： 近年来运用进化算法（EAs）解决多目标优化问题（Multi-objective Optimization Problems MOPs）引起了各国学者们的关注。作为一种基于种群的优化方法，EAs提供了一种在一次运行后得到一组优化的解的方法。差分进化（DE）算法是EA的一个分支，最开始是用来解决连续函数空间的问题。提出了一种改进的基于差分进化的多目标进化算法（CDE），并且将它与另外两个经典的多目标进化算法（MOEAs）NSGA-II和SPEA2进行了对比实验。

关键词: 多目标优化, 差分进化, 多目标进化算法（CDE）

LI Ke,ZHENG Jin-hua. Improved multi-objective evolutionary algorithm based on differential evolution[J]. Computer Engineering and Applications, 2008, 44(29): 51-56.

李珂,郑金华. 一种改进的基于差分进化的多目标进化算法[J]. 计算机工程与应用, 2008, 44(29): 51-56.

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Improved multi-objective evolutionary algorithm based on differential evolution

一种改进的基于差分进化的多目标进化算法

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