Integrating Particle Swarm Optimization with Stochastic Point Location method in noisy environment

Junqi Zhang, Siyu Lu, Di Zang, Mengchu Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Particle Swarm Optimization (PSO) deteriorates when facing a high-noise environment. To address this issue, one popular mechanism is the resampling method that is based on re-evaluations to find the true fitness value. However, the budget for re-evaluations in PSO is limited. In this paper, we intend to integrate a Stochastic Point Location (SPL) method into PSO to alleviate the impacts of noise on the evaluation of true fitness. SPL deals with the problem of a learning mechanism locating a target point on the line in noisy environment. Up to now, Adaptive Step Searching is the fastest algorithm in solving the SPL problem and shows great anti-noise performance. This paper investigates two effective hybrid PSO approaches, by integrating PSO and PSO-Equal Resampling with Adaptive Step Searching. The simulation results and comparisons on 20 large-scale benchmark optimization functions in noisy environments demonstrate the superiority of the proposed approaches in terms of optimization accuracy and convergence rate.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2067-2072
Number of pages6
ISBN (Electronic)9781509018970
DOIs
StatePublished - Feb 6 2017
Event2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Budapest, Hungary
Duration: Oct 9 2016Oct 12 2016

Publication series

Name2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings

Other

Other2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016
Country/TerritoryHungary
CityBudapest
Period10/9/1610/12/16

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Control and Optimization
  • Human-Computer Interaction

Keywords

  • Adaptive Step Searching
  • Noisy Environment
  • Particle Swarm Optimization

Fingerprint

Dive into the research topics of 'Integrating Particle Swarm Optimization with Stochastic Point Location method in noisy environment'. Together they form a unique fingerprint.

Cite this