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A novel hybrid particle swarm optimizer: Tradeoff between exploration and exploitation

  • Xi'an Jiaotong University
  • Xidian University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Hybridization is a useful method to enhance the performance of particle swarm optimizer (PSO). In this paper, a novel particle swarm optimizer (NHPSO) combining PSO with a constriction factor (CF-PSO) and the fully informed particle swarm optimizer (FIPSO) in cycles is proposed, in order to balance the convergence speed and search accuracy. Six most commonly used benchmarks are used to evaluate the strategy on the performance of PSOs. The results suggest NHPSO has a generally good performance in numerical optimization.

Original languageEnglish
Title of host publicationICINIS 2009 - Proceedings of the 2nd International Conference on Intelligent Networks and Intelligent Systems
Pages457-460
Number of pages4
DOIs
StatePublished - 2009
Externally publishedYes
Event2nd International Conference on Intelligent Networks and Intelligent Systems, ICINIS 2009 - Tianjin, China
Duration: 1 Nov 20093 Nov 2009

Publication series

NameICINIS 2009 - Proceedings of the 2nd International Conference on Intelligent Networks and Intelligent Systems

Conference

Conference2nd International Conference on Intelligent Networks and Intelligent Systems, ICINIS 2009
Country/TerritoryChina
CityTianjin
Period1/11/093/11/09

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