Simulation-optimization under uncertainty through metamodeling and bootstrapping

Dellino, Gabriella and Kleijnen, Jack P.C. and Meloni, Carlo Simulation-optimization under uncertainty through metamodeling and bootstrapping. Procedia - Social and Behavioral Sciences, 2 (6). 7640 - 7641. ISSN 1877-0428 (2010)

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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 (Gaussian Process) metamodels (response surfaces). These metamodels are combined with Non-Linear Mathematical Programming (NLMP) to find a robust optimal solution. Varying the constraint values in the NLMP model gives an estimated Pareto frontier. To account for the variability of the estimated Pareto frontier, this research uses bootstrapping which gives confidence regions for the robust optimal solution. This methodology is illustrated through the Economic Order Quantity (EOQ) inventory-management model, accounting for the uncertainties in the demand rate and the cost coefficients.

Item Type:	Article
Identification Number:	https://doi.org/10.1016/j.sbspro.2010.05.156
Additional Information:	Sixth International Conference on Sensitivity Analysis of Model Output
Uncontrolled Keywords:	Simulation-optimization; Uncertainty; Robustness; Metamodel; Bootstrap
Subjects:	Q Science > QA Mathematics T Technology > T Technology (General)
Research Area:	Economics and Institutional Change
Depositing User:	Users 17 not found.
Date Deposited:	30 Nov 2012 08:34
Last Modified:	30 Nov 2012 08:34
URI:	http://eprints.imtlucca.it/id/eprint/1441

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• Simulation-optimization under uncertainty through metamodeling and bootstrapping. (deposited 01 Aug 2011 13:00)
  • Simulation-optimization under uncertainty through metamodeling and bootstrapping. (deposited 30 Nov 2012 08:34) [Currently Displayed]

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