Cover Image
QR Code

A new logistic dynamic particle swarm optimization algorithm based on random topology.

Population topology of particle swarm optimization (PSO) will directly affect the dissemination of optimal information during the evolutionary process and will have a significant impact on the performance of PSO. Classic static population topologies are usually used in PSO, such as fully connected t...

Full description

Published in:Scientific World Journal pp. 409167 - 409168
Main Authors: Ni, Qingjian, Deng, Jianming
Format: research Journal Article
Published: Wiley-Blackwell 2013
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104165192&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 104165192
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        1537744X
        1BX5
      jtl: Scientific World Journal
      issn: 1537744X
      maglogo: N
    pubinfo:
      dt: 2013
      pid: 480
      pub: Wiley-Blackwell
      place: Malden, Massachusetts
    artinfo:
      ui:
        104165192
        104165192
        NLM23818820
        2012242143
        10.1155/2013/409167
        NLM23818820
        PMC3683496
        104165192
      ppf: 409167
      ppct: 1
      formats:
      tig:
        atl: A new logistic dynamic particle swarm optimization algorithm based on random topology.
      aug:
        au:
          Ni, Qingjian
          Deng, Jianming
        affil: School of Computer Science and Engineering, Southeast University, Nanjing 211189, China ; Provincial Key Laboratory for Computer Information Processing Technology, Soochow University, Suzhou 215006, China.
      sug:
        subj:
          Particle Swarm Optimization
          Logistic Regression
          Computer Simulation
      ab: Population topology of particle swarm optimization (PSO) will directly affect the dissemination of optimal information during the evolutionary process and will have a significant impact on the performance of PSO. Classic static population topologies are usually used in PSO, such as fully connected topology, ring topology, star topology, and square topology. In this paper, the performance of PSO with the proposed random topologies is analyzed, and the relationship between population topology and the performance of PSO is also explored from the perspective of graph theory characteristics in population topologies. Further, in a relatively new PSO variant which named logistic dynamic particle optimization, an extensive simulation study is presented to discuss the effectiveness of the random topology and the design strategies of population topology. Finally, the experimental data are analyzed and discussed. And about the design and use of population topology on PSO, some useful conclusions are proposed which can provide a basis for further discussion and research.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N