Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (22): 187-190.DOI: 10.3778/j.issn.1002-8331.2009.22.060

• 工程与应用 • Previous Articles     Next Articles

Multi-objective particle swarm optimization and its application in space layout optimization of groundwater

JIANG Qing,HU Hai-ying,WANG Ru-jing   

  1. Institute of Intelligent Machine,Chinese Academy of Sciences,Hefei 230031,China
  • Received:2008-04-21 Revised:2008-07-25 Online:2009-08-01 Published:2009-08-01
  • Contact: JIANG Qing

MOPSO算法及其在地下水监测网布局优化中的应用

蒋 庆,胡海瀛,王儒敬   

  1. 中国科学院 合肥智能机械研究所,合肥 230031
  • 通讯作者: 蒋 庆

Abstract: In this paper,an improved version of CMOPSO,ICMOPSO,is proposed.ICMOPSO adopts a novel strategy called particle angle division to update archive and select the global best guide from archive.Moreover,a new particle updating strategy is proposed to deal with the problem of premature convergence and diversity maintenance within the swarm.The algorithm is applied to solve multi-objecitve layout optimization of groundwater monitoring network.The simulation performance indicates the effectiveness of the presented algorithm with regard to solving the large scale complex multi-objective optimization problem.

Key words: particle swarm optimization, multi-objective optimization, Shule river, groundwater monitoring network, space layout

摘要: 在已有多目标粒子群优化算法(CMOPSO)研究和分析的基础上,为提高算法的聚合性和分布性,设计了一种新的精英档案维护及全局最优值选取策略,同时,使用动态全局最优值设置策略对原有算法的粒子速度更新公式进行扩展,以增强粒子的搜索能力,克服早熟现象。通过对疏勒河项目区地下水监测网空间布局多目标优化计算,表明该算法是求解大规模复杂多目标优化问题的一种有效手段。

关键词: 粒子群优化, 多目标优化, 疏勒河灌区, 地下水监测网, 空间布局