eprintid: 753
rev_number: 10
eprint_status: archive
userid: 17
dir: disk0/00/00/07/53
datestamp: 2011-08-01 12:52:38
lastmod: 2011-08-04 07:30:21
status_changed: 2011-08-01 12:52:38
type: book_section
metadata_visibility: show
item_issues_count: 0
creators_name: Dellino, Gabriella
creators_name: Kleijnen, Jack P.C.
creators_name: Meloni, Carlo
creators_id: gabriella.dellino@imtlucca.it
creators_id: 
creators_id: 
title: Parametric and distribution-free bootstrapping in robust simulation-optimization
ispublished: pub
subjects: QA
subjects: TK
divisions: EIC
full_text_status: none
keywords: Gaussian process; Kriging metamodels; Pareto frontier estimation; Taguchi world view; distribution-free bootstrapping; nonlinear mathematical programming; regression metamodel; robust simulation-optimization
abstract: Most methods in simulation-optimization assume known environments, whereas this research accounts for uncertain environments combining Taguchi's world view with either regression or Kriging (also called Gaussian Process) metamodels (emulators, response surfaces, surrogates). These metamodels are combined with Non-Linear Mathematical Programming (NLMP) to find robust solutions. Varying the constraint values in this NLMP gives an estimated Pareto frontier. To account for the variability of this estimated Pareto frontier, this contribution considers different bootstrap methods to obtain confidence regions for a given solution. This methodology is illustrated through some case studies selected from the literature.
date: 2010-12
date_type: published
publisher: IEEE
pagerange: 1283 -1294
event_title: Winter Simulation Conference (WSC), Proceedings of the 2010
id_number: 10.1109/WSC.2010.5679064
refereed: TRUE
isbn: 978-1-4244-9866-6 
book_title: Winter Simulation Conference (WSC)
official_url: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5679064&isnumber=5678856
citation:   Dellino, Gabriella and Kleijnen, Jack P.C. and Meloni, Carlo  Parametric and distribution-free bootstrapping in robust simulation-optimization.   In:  Winter Simulation Conference (WSC).   IEEE, 1283 -1294.  ISBN 978-1-4244-9866-6       (2010)