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   

  1. 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   

  1. 湘潭大学 信息工程学院,湖南 湘潭 411105

  • 通讯作者: 李 珂

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)