Heterogeneous Particle Swarm Optimizer and its Application in Aircraft Manufacturing Logistics

Yulian Cao, Mengchu Zhou, Wenfeng Li, Gabriel Lodewijks

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

Abstract

Particle swarm optimization (PSO) attracts much attention due to its ability in solving complex practical engineering problems effectively. To further improve its performance, a heterogeneous particle swarm optimizer (HPSO) is proposed in this work. Five widely used benchmark functions are selected to test its efficiency. Furthermore, five state-of-the-art improved PSO variants are selected for a comparisons purpose. The results demonstrate that HPSO is better than the other five algorithms. A logistics problem in aircraft manufacturing is then studied and solved. The results show HPSO's superiority over its tested PSO variants.

Original languageEnglish (US)
Title of host publication2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728168531
DOIs
StatePublished - Oct 30 2020
Event2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020 - Nanjing, China
Duration: Oct 30 2020Nov 2 2020

Publication series

Name2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020

Conference

Conference2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020
Country/TerritoryChina
CityNanjing
Period10/30/2011/2/20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Statistics, Probability and Uncertainty
  • Control and Optimization
  • Sensory Systems

Keywords

  • aircraft manufacturing logistics
  • evolutionary computation
  • facility location
  • particle swarm optimizer (PSO)

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