A fast and elitist multi-objective particle swarm algorithm: NSPSO

Yang Liu*

*Corresponding author for this work

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

24 Citations (Scopus)

Abstract

In this paper, a new nondominated sorting particle swarm optimisation (NSPSO), is proposed, that combines the operations (fast ranking of nondominated solutions, crowding distance ranking and elitist strategy of combining parent population and offspring population together) of a known MOGA NSGA-II and the other advanced operations (selection and mutation operations) with a single particle swarm optimiser (PSO). The efficacy of this algorithm is demonstrated on 2 test functions, and the comparison is made with the NSGA-II and a Multi-objective PSO (MOPSO-CD). The simulation results suggest that the proposed optimisation framework is able to achieve good solutions as well diversity compared to NSGA-II and MOPSO-CD optimisation framework.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Granular Computing, GRC 2008
Pages470-475
Number of pages6
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 IEEE International Conference on Granular Computing, GRC 2008 - Hangzhou, China
Duration: 26 Aug 200828 Aug 2008

Publication series

Name2008 IEEE International Conference on Granular Computing, GRC 2008

Conference

Conference2008 IEEE International Conference on Granular Computing, GRC 2008
Country/TerritoryChina
CityHangzhou
Period26/08/0828/08/08

Fingerprint

Dive into the research topics of 'A fast and elitist multi-objective particle swarm algorithm: NSPSO'. Together they form a unique fingerprint.

Cite this