Processing Parameters Optimization Based on PSO Algorithm

Particle swarm optimization (PSO) is classified into swarm intelligence algorithm. Focusing on the NC processing parameters optimization, this paper has made several improvements on PSO: dividing solutions into feasible and infeasible, then shrinking the infeasible solutions; dividing feasible solut...

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Veröffentlicht in:Applied Mechanics and Materials 2012-01, Vol.141, p.419-423
Hauptverfasser: Wu, Rong Zong, Shao, Ming Kun, Liu, Qing Jian, Wang, Run
Format: Artikel
Sprache:eng
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Zusammenfassung:Particle swarm optimization (PSO) is classified into swarm intelligence algorithm. Focusing on the NC processing parameters optimization, this paper has made several improvements on PSO: dividing solutions into feasible and infeasible, then shrinking the infeasible solutions; dividing feasible solutions into inferior and non-inferior, then choosing the non-inferior solution with most domination solutions as the global best position for inferior solutions. It has shown a significant achievement in actual processing.
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.141.419