eprintid: 1444
rev_number: 12
eprint_status: archive
userid: 17
dir: disk0/00/00/14/44
datestamp: 2012-12-14 08:26:02
lastmod: 2014-01-29 13:54:33
status_changed: 2012-12-14 08:26:02
type: book_section
metadata_visibility: show
creators_name: Dellino, Gabriella
creators_name: Meloni, Carlo
creators_id: gabriella.dellino@imtlucca.it
creators_id: 
title: Metamodel variability analysis combining bootstrapping and validation techniques
ispublished: pub
subjects: HA
subjects: QA
divisions: EIC
full_text_status: public
pres_type: paper
note: Article No.: 334
abstract: Research on metamodel-based optimization has received considerably increasing interest in recent years, and has found successful applications in solving computationally expensive problems. The joint use of computer simulation experiments and metamodels introduces a source of uncertainty that we refer to as metamodel variability. To analyze and quantify this variability, we apply bootstrapping to residuals derived as prediction errors computed from cross-validation. The proposed method can be used with different types of metamodels, especially when limited knowledge on parameters’ distribution is available or when a limited computational budget is allowed. Our preliminary experiments based on the robust version of
the EOQ model show encouraging results.
date: 2012-12
date_type: published
publisher: ACM
event_title: Winter Simulation Conference 2012
event_location: Berlin, Germany
event_dates: December 9-12, 2012
event_type: conference
refereed: TRUE
isbn: 978-1-4673-4780-8
book_title: WSC '12 Proceedings of the Winter Simulation Conference 
official_url: http://dl.acm.org/citation.cfm?id=2430206
citation:   Dellino, Gabriella and Meloni, Carlo  Metamodel variability analysis combining bootstrapping and validation techniques.   In:  WSC '12 Proceedings of the Winter Simulation Conference.   ACM.  ISBN 978-1-4673-4780-8      (2012)  
document_url: http://eprints.imtlucca.it/1444/1/wsc12poster-dellino_final.pdf