TY - GEN
T1 - A note on the subset selection for simulation optimization
AU - Gao, Siyang
AU - Chen, Weiwei
PY - 2015/12
Y1 - 2015/12
N2 - In this paper, we consider the problem of selecting an optimal subset from a finite set of simulated designs. Using the optimal computing budget allocation (OCBA) framework, we formulate the problem as that of maximizing the probability of correctly selecting the top m designs subject to a constraint on the total number of samples available. For an approximation of the probability of correct selection, we derive an asymptotically optimal subset selection procedure that is easy to implement. More importantly, we provide some useful insights on characterizing an efficient subset selection rule and how it can be achieved by adjusting the budgets allocated to the optimal and non-optimal subsets.
AB - In this paper, we consider the problem of selecting an optimal subset from a finite set of simulated designs. Using the optimal computing budget allocation (OCBA) framework, we formulate the problem as that of maximizing the probability of correctly selecting the top m designs subject to a constraint on the total number of samples available. For an approximation of the probability of correct selection, we derive an asymptotically optimal subset selection procedure that is easy to implement. More importantly, we provide some useful insights on characterizing an efficient subset selection rule and how it can be achieved by adjusting the budgets allocated to the optimal and non-optimal subsets.
UR - https://www.scopus.com/pages/publications/84962850779
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84962850779&origin=recordpage
U2 - 10.1109/WSC.2015.7408534
DO - 10.1109/WSC.2015.7408534
M3 - RGC 32 - Refereed conference paper (with host publication)
VL - 2015
SP - 3768
EP - 3776
BT - Proceedings of the 2015 Winter Simulation Conference
PB - IEEE
T2 - Winter Simulation Conference, WSC 2015
Y2 - 6 December 2015 through 9 December 2015
ER -