An improved particle swarm algorithm applied to the price structure optimization of the bankcard network

被引:0
|
作者
Song Dan [1 ]
Huang Xiao-yan [2 ]
机构
[1] Dalian Univ Technol, Inst Syst Engn, Dalian 116023, Peoples R China
[2] Fudan Univ, Appl Econ Postdoctoral Mobile Stn, Shanghai 200433, Peoples R China
基金
中国国家自然科学基金;
关键词
bankcard network; optimization model; particle swarm optimization; price structure;
D O I
暂无
中图分类号
F [经济];
学科分类号
02 ;
摘要
The price structure of the bankcard network is vital in deciding the prosperity of the bankcard transaction market. In order to obtain the optimal price structure of the bankcard network, a constraint optimization model is constructed and the particle swarm optimization (PSO) algorithm is introduced and improved by adding a perturbation factor, adopting double fitness value and keeping some unsuitable solutions near the boundary. By applying the improved PSO algorithm, the optimal solution is given and the policy implication is provided to promote the development of the bankcard network. Simultaneously, the improved PSO algorithm is proved to be an effective and efficient way to solve the constraint optimal problems.
引用
收藏
页码:1666 / +
页数:3
相关论文
共 50 条
  • [21] Application of an improved particle swarm optimization algorithm for neural network training
    Zhao, FQ
    Ren, ZY
    Yu, DM
    Yang, YH
    [J]. PROCEEDINGS OF THE 2005 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS AND BRAIN, VOLS 1-3, 2005, : 1693 - 1698
  • [22] An Improved Particle Swarm Optimization Algorithm Applied to the Unified Evaluation of Circularity Error
    Wu, Zhongyong
    Gou, Jin
    Cui, Changcai
    [J]. FRONTIERS OF MANUFACTURING AND DESIGN SCIENCE, PTS 1-4, 2011, 44-47 : 3937 - +
  • [23] Compound decision model for bankcard network's price structure and bankcard consumption
    Huang, Xiao-Yan
    Hu, Xiang-Pei
    Bao, Hong-Yang
    [J]. Dalian Ligong Daxue Xuebao/Journal of Dalian University of Technology, 2007, 47 (05): : 767 - 772
  • [24] Constrained optimization with an improved particle swarm optimization algorithm
    Munoz Zavala, Angel E.
    Hernandez Aguirre, Arturo
    Villa Diharce, Enrique R.
    Botello Rionda, Salvador
    [J]. INTERNATIONAL JOURNAL OF INTELLIGENT COMPUTING AND CYBERNETICS, 2008, 1 (03) : 425 - 453
  • [25] Bayesian network structure learning based on improved particle swarm optimization
    [J]. Gao, Xiaoguang, 1600, Northwestern Polytechnical University (32):
  • [26] An Improved Particle Swarm Optimization Algorithm with Immunity
    Jiao Wei
    Liu Guang-bin
    [J]. ICICTA: 2009 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL I, PROCEEDINGS, 2009, : 241 - 244
  • [27] An Improved Particle Swarm Algorithm for Search Optimization
    Li Zhi-jie
    Liu Xiang-dong
    Duan Xiao-dong
    Wang Cun-rui
    [J]. PROCEEDINGS OF THE 2009 WRI GLOBAL CONGRESS ON INTELLIGENT SYSTEMS, VOL I, 2009, : 154 - 158
  • [28] An improved particle swarm optimization algorithm with disturbance
    Jian, W
    Xue, YC
    Qian, JX
    [J]. 2004 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN & CYBERNETICS, VOLS 1-7, 2004, : 5900 - 5904
  • [29] An Optimization Algorithm on Improved Chaos Particle Swarm
    Cao, Jian
    Cao, Zeyang
    Gong, Xiaopeng
    Li, Gang
    [J]. INTERNATIONAL CONFERENCE ON ELECTRICAL AND CONTROL ENGINEERING (ICECE 2015), 2015, : 413 - 416
  • [30] An Improved Probability Particle Swarm Optimization Algorithm
    Lu, Qiang
    Qiu, Xuena
    [J]. ADVANCES IN SWARM INTELLIGENCE, PT 1, PROCEEDINGS, 2010, 6145 : 102 - +