Aus Aifbportal
Version vom 9. Juli 2012, 11:17 Uhr von Psh (Diskussion | Beiträge) (Die Seite wurde neu angelegt: „{{Publikation Erster Autor |ErsterAutorNachname=Cipold |ErsterAutorVorname=Michael }} {{Publikation Author |Rank=2 |Author=Pradyumn Kumar Shukla }} {{Publikation …“)
(Unterschied) ← Nächstältere Version | Aktuelle Version (Unterschied) | Nächstjüngere Version → (Unterschied)
Wechseln zu:Navigation, Suche

An Evolutionary Optimization Approach for Bulk Material Blending Systems

Published: 2012 September

Buchtitel: Parallel Problem Solving from Nature - PPSN XII
Reihe: Lecture Notes in Computer Science
Verlag: Springer

Referierte VeröffentlichungNote: Accepted for publication in PPSN 2012


Bulk material blending systems still mostly implement static and non-reactive material blending methods like the well-known Chevron stacking. The optimization potential in the existing systems which can be made available using quality analyzing methods as online X-ray fluorescence measurement is inspected in detail in this paper using a multi-objective optimization approach based on steady state evolutionary algorithms. We propose various Baldwinian and Lamarckian repair algorithms, test them on real world problem data and deliver optimized solutions which outperform the standard techniques.


Effiziente Algorithmen


Evolutionäre Algorithmen, Multikriterielle Optimierung, Optimierung