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An improved niche ant colony algorithm for multi-modal function optimization

  • Xinming Zhang*
  • , Lirong Wang
  • , Bingyi Huang
  • *Corresponding author for this work
  • Harbin Institute of Technology Shenzhen
  • Xingtai Vocational and Technical College

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

Abstract

In this paper, to overcome the premature defect of traditional ant colony algorithm, a new improved niche ant colony algorithm (niche ant colony algorithm based on the fitness sharing principle) is proposed by combining the fitness sharing method with niche ant colony algorithm and applied to the multi-modal function optimization problem. The comparison between the results obtained by the improved niche ant colony algorithm (INACA) and the results found by traditional ant colony algorithm(ACA) and niche genetic algorithm(NGA) shows that the former has higher effectiveness and superiority in global optimization.

Original languageEnglish
Title of host publicationProceedings - 2012 International Symposium on Instrumentation and Measurement, Sensor Network and Automation, IMSNA 2012
Pages403-406
Number of pages4
DOIs
StatePublished - 2012
Externally publishedYes
Event2012 International Symposium on Instrumentation and Measurement, Sensor Network and Automation, IMSNA 2012 - Sanya, Hainan, China
Duration: 25 Aug 201228 Aug 2012

Publication series

NameProceedings - 2012 International Symposium on Instrumentation and Measurement, Sensor Network and Automation, IMSNA 2012
Volume2

Conference

Conference2012 International Symposium on Instrumentation and Measurement, Sensor Network and Automation, IMSNA 2012
Country/TerritoryChina
CitySanya, Hainan
Period25/08/1228/08/12

Keywords

  • fitness sharing
  • improved niche ant colony algorithm
  • multi-modal function optimization

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