TY  - JOUR
UR  - http://www.sciencedirect.com/science/article/pii/S1877042810012978
PB  - Elsevier
KW  - Simulation-optimization; Uncertainty; Robustness; Metamodel; Bootstrap
SN  - 1877-0428
JF  - Procedia - Social and Behavioral Sciences
ID  - eprints1441
Y1  - 2010///
EP  -  7641
AV  - public
SP  - 7640 
A1  - Dellino, Gabriella
A1  - Kleijnen, Jack P.C.
A1  - Meloni, Carlo
N2  - 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.
VL  - 2
IS  - 6
N1  - Sixth International Conference on Sensitivity Analysis of Model Output
TI  - Simulation-optimization under uncertainty through metamodeling and bootstrapping
ER  -