An improved cooperative quantum-behaved particle swarm optimization

被引：61
|
作者：
Li, Yangyang [1 ]
Xiang, Rongrong [1 ]
Jiao, Licheng [1 ]
Liu, Ruochen [1 ]
机构：
[1] Xidian Univ, Minist Educ China, Key Lab Intelligent Percept & Image Understanding, Xian 710071, Peoples R China
来源：
SOFT COMPUTING | 2012年 / 16卷 / 06期
基金：
中国博士后科学基金; 中国国家自然科学基金;
关键词：
Particle swarm optimization; Quantum-behaved; Cooperative quantum-behaved particle swarm optimization; Composition functions;
D O I：
10.1007/s00500-012-0803-y
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Particle swarm optimization (PSO) is a population-based stochastic optimization. Its parameters are easy to control, and it operates easily. But, the particle swarm optimization is a local convergence algorithm. Quantum-behaved particle swarm optimization (QPSO) overcomes this shortcoming, and outperforms original PSO. Based on classical QPSO, cooperative quantum-behaved particle swarm optimization (CQPSO) is present. This CQPSO, a particle firstly obtaining several individuals using Monte Carlo method and these individuals cooperate between them. In the experiments, five benchmark functions and six composition functions are used to test the performance of CQPSO. The results show that CQPSO performs much better than the other improved QPSO in terms of the quality of solution and computational cost.
引用
收藏
页码：1061 / 1069
页数：9
相关论文
共 50 条
  • [1] An improved cooperative quantum-behaved particle swarm optimization
    Yangyang Li
    Rongrong Xiang
    Licheng Jiao
    Ruochen Liu
    [J]. Soft Computing, 2012, 16 : 1061 - 1069
  • [2] A cooperative approach to quantum-behaved particle swarm optimization
    Gao, Hao
    Xu, Wenbo
    Gao, Tao
    [J]. 2007 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING, CONFERENCE PROCEEDINGS BOOK, 2007, : 205 - +
  • [3] A cooperative approach to quantum-behaved particle swarm optimization
    Kang, Yan
    Xu, Wenbo
    Sun, Jun
    [J]. PROGRESS IN INTELLIGENCE COMPUTATION AND APPLICATIONS, PROCEEDINGS, 2007, : 332 - 337
  • [4] An improved quantum-behaved particle swarm optimization algorithm
    Panchi Li
    Hong Xiao
    [J]. Applied Intelligence, 2014, 40 : 479 - 496
  • [5] An Improved Quantum-Behaved Particle Swarm Optimization Algorithm
    Yang, Jie
    Xie, Jiahua
    [J]. 2010 2ND INTERNATIONAL ASIA CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS (CAR 2010), VOL 2, 2010, : 159 - 162
  • [6] An improved quantum-behaved particle swarm optimization algorithm
    Li, Panchi
    Xiao, Hong
    [J]. APPLIED INTELLIGENCE, 2014, 40 (03) : 479 - 496
  • [7] A New Improved Quantum-behaved Particle Swarm Optimization Model
    Huang, Zhen
    Wang, Yongji
    Yang, Chuanjiang
    Wu, Chaozhong
    [J]. ICIEA: 2009 4TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-6, 2009, : 1551 - +
  • [8] An Improved Quantum-Behaved Particle Swarm Optimization for Endmember Extraction
    Du, Bo
    Wei, Qiuci
    Liu, Rong
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2019, 57 (08): : 6003 - 6017
  • [9] Quantum-behaved Particle Swarm Optimization with Cooperative-Competitive Coevolutionary
    Lu, Songfeng
    Sun, Chengfu
    [J]. KAM: 2008 INTERNATIONAL SYMPOSIUM ON KNOWLEDGE ACQUISITION AND MODELING, PROCEEDINGS, 2008, : 593 - 597
  • [10] Coevolutionary Quantum-behaved Particle Swarm Optimization with Hybrid Cooperative Search
    Lu, Songfeng
    Sun, Chengfu
    [J]. PACIIA: 2008 PACIFIC-ASIA WORKSHOP ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION, VOLS 1-3, PROCEEDINGS, 2008, : 105 - 109
12345