Inproceedings1410: Unterschied zwischen den Versionen
K (Added from ontology) |
Uri (Diskussion | Beiträge) |
||
(2 dazwischenliegende Versionen von einem anderen Benutzer werden nicht angezeigt) | |||
Zeile 1: | Zeile 1: | ||
+ | {{Publikation Erster Autor | ||
+ | |ErsterAutorNachname=Ireland | ||
+ | |ErsterAutorVorname=David | ||
+ | }} | ||
{{Publikation Author | {{Publikation Author | ||
− | |Rank= | + | |Rank=2 |
− | |Author= | + | |Author=Andrew Lewis |
}} | }} | ||
{{Publikation Author | {{Publikation Author | ||
Zeile 8: | Zeile 12: | ||
}} | }} | ||
{{Publikation Author | {{Publikation Author | ||
− | |Rank= | + | |Rank=3 |
− | |Author= | + | |Author=Sanaz Mostaghim |
− | |||
− | |||
− | |||
− | |||
}} | }} | ||
{{Inproceedings | {{Inproceedings | ||
Zeile 22: | Zeile 22: | ||
|Booktitle=eSceience Conference | |Booktitle=eSceience Conference | ||
|Pages=auf CD erschienen | |Pages=auf CD erschienen | ||
− | |Publisher=IEEE Computer Society | + | |Publisher=IEEE Computer Society Washington, DC, USA |
}} | }} | ||
{{Publikation Details | {{Publikation Details | ||
|Abstract=This paper presents quantitative comparison of the performance of different methods for selecting the guide particle for multi-objective particle swarm optimization (MOPSO). Two principal methods are compared: the recently described Sigma method, and a new "Centroid" method. Drawing on the different dominant behaviors exhibited by the different selection methods, a variety of hybridizations of these is proposed to develop a more robust optimization algorithm. Statistical analysis of the hybrid methods demonstrates their contribution to improved performance of the optimization algorithm. | |Abstract=This paper presents quantitative comparison of the performance of different methods for selecting the guide particle for multi-objective particle swarm optimization (MOPSO). Two principal methods are compared: the recently described Sigma method, and a new "Centroid" method. Drawing on the different dominant behaviors exhibited by the different selection methods, a variety of hybridizations of these is proposed to develop a more robust optimization algorithm. Statistical analysis of the hybrid methods demonstrates their contribution to improved performance of the optimization algorithm. | ||
|ISBN=0-7695-2734-5 | |ISBN=0-7695-2734-5 | ||
− | + | |Forschungsgruppe=Effiziente Algorithmen | |
− | |||
− | |||
− | |||
− | |Forschungsgruppe= | ||
}} | }} |
Aktuelle Version vom 24. September 2009, 16:55 Uhr
Hybrid Particle Guide Selection Methods in Multi-Objective Particle Swarm Optimization
Hybrid Particle Guide Selection Methods in Multi-Objective Particle Swarm Optimization
Published: 2006
Dezember
Buchtitel: eSceience Conference
Seiten: auf CD erschienen
Verlag: IEEE Computer Society Washington, DC, USA
Referierte Veröffentlichung
BibTeX
Kurzfassung
This paper presents quantitative comparison of the performance of different methods for selecting the guide particle for multi-objective particle swarm optimization (MOPSO). Two principal methods are compared: the recently described Sigma method, and a new "Centroid" method. Drawing on the different dominant behaviors exhibited by the different selection methods, a variety of hybridizations of these is proposed to develop a more robust optimization algorithm. Statistical analysis of the hybrid methods demonstrates their contribution to improved performance of the optimization algorithm.
ISBN: 0-7695-2734-5