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 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
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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. |
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ISSN: | 1660-9336 1662-7482 1662-7482 |
DOI: | 10.4028/www.scientific.net/AMM.141.419 |