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The application of an improved PSO based on the quantum genetic algorithm in the submersible path-planning

  • Fei Yu*
  • , Yang Lei Liu
  • *Corresponding author for this work
  • Harbin Engineering University

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

Abstract

An improved particle swarm optimization algorithm (PSO) combined with quantum genetic algorithm is proposed, to solve the problems that the PSO is difficult to converge for benchmark complex problems and it's parameters are hard to define. The new algorithm is used for submersible path planning and simulation on some standard test functions. The results show that the improved is superior to the standard PSO in optimization ability and the convergence rate, and it can find the optimal path faster.

Original languageEnglish
Title of host publication2011 3rd International Workshop on Intelligent Systems and Applications, ISA 2011 - Proceedings
DOIs
StatePublished - 2011
Externally publishedYes
Event2011 3rd International Workshop on Intelligent Systems and Applications, ISA 2011 - Wuhan, China
Duration: 28 May 201129 May 2011

Publication series

Name2011 3rd International Workshop on Intelligent Systems and Applications, ISA 2011 - Proceedings

Conference

Conference2011 3rd International Workshop on Intelligent Systems and Applications, ISA 2011
Country/TerritoryChina
CityWuhan
Period28/05/1129/05/11

Keywords

  • particle swarm optimization
  • path-planning
  • quantum genetic algorithm
  • submarine

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