Home |  ENGLISH |  Kontakt |  Impressum |  Anmelden |  KIT

Inproceedings3298

Aus Aifbportal

Wechseln zu: Navigation, Suche

(This page contains COinS metadata)

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 Veröffentlichung
Note: Accepted for publication in PPSN 2012.
BibTeX

Kurzfassung
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.



Forschungsgruppe

Effiziente Algorithmen


Forschungsgebiet
Evolutionäre Algorithmen, Multikriterielle Optimierung, Optimierung


-->