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)Full text not available from this repository.
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.
|Item Type:||Book Section|
|Uncontrolled Keywords:||Gaussian process; Kriging metamodels; Pareto frontier estimation; Taguchi world view; distribution-free bootstrapping; nonlinear mathematical programming; regression metamodel; robust simulation-optimization|
|Subjects:||Q Science > QA Mathematics
T Technology > TK Electrical engineering. Electronics Nuclear engineering
|Research Area:||Economics and Institutional Change|
|Depositing User:||Users 17 not found.|
|Date Deposited:||01 Aug 2011 12:52|
|Last Modified:||04 Aug 2011 07:30|
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