eprintid: 761
rev_number: 9
eprint_status: archive
userid: 17
dir: disk0/00/00/07/61
datestamp: 2011-08-02 09:36:48
lastmod: 2011-08-04 07:30:21
status_changed: 2011-08-02 09:36:48
type: monograph
metadata_visibility: no_search
item_issues_count: 0
creators_name: Dellino, Gabriella
creators_name: Meloni, Carlo
creators_id: gabriella.dellino@imtlucca.it
creators_id: 
title: Metamodel variability in robust simulation-optimization: a bootstrap analysis
ispublished: unpub
subjects: HB
subjects: QA
subjects: QA75
divisions: EIC
full_text_status: none
monograph_type: technical_report
keywords: Simulation-optimization; metamodels; validation; bootstrap
abstract: Metamodels are often used in simulation-optimization for the design and management of complex systems. These metamodels yield insight into the relationship between responses and decision variables, providing fast analysis tools instead of the more expensive computer simulations. Moreover, these metamodels enable the integration of discipline-dependent analysis into the overall decision
process. The use of stochastic simulation experiments and metamodels introduces a source of uncertainty in the decision process that we refer to as metamodel variability. To quantify this variability, we use bootstrapping. More speci�cally, we combine cross-validation and bootstrapping to simulate the metamodel construction process in stochastic environments. The resulting methodology
is illustrated through the well-known Economic Order Quantity (EOQ) model using Kriging and regression metamodels. The relative validation errors are small, so they suggest that the metamodels give an adequate  approximation, and bootstrapping these errors allows us to quantify the metamodels' variability in an acceptable way.
date: 2011
pages: 29
institution: Università degli studi di Siena
department: Dipartimento di ingegneria dell'informazione
official_url: http://www.dii.unisi.it/priv/papers/papers_doc/49.pdf
citation:   Dellino, Gabriella and Meloni, Carlo  Metamodel variability in robust simulation-optimization: a bootstrap analysis.  Technical Report       (Unpublished)