| 1 |
An efficient simulation procedure for ranking the top simulated designs in the presence of stochastic constraints
Xiao H, Chen H, Lee LH
Automatica, 103, 106, 2019 |
| 2 |
Efficient simulation budget allocation for subset selection using regression metamodels
Gao F, Shi ZS, Gao SY, Xiao H
Automatica, 106, 192, 2019 |
| 3 |
Optimal Computing Budget Allocation to Select the Nondominated Systems-A Large Deviations Perspective
Li JX, Liu WZ, Pedrielli G, Lee LH, Chew EP
IEEE Transactions on Automatic Control, 63(9), 2913, 2018 |
| 4 |
Simulation Budget Allocation for Selecting the Top-m Designs With Input Uncertainty
Xiao H, Gao SY
IEEE Transactions on Automatic Control, 63(9), 3127, 2018 |
| 5 |
Robust ranking and selection with optimal computing budget allocation
Gao SY, Xiao H, Zhou E, Chen WW
Automatica, 81, 30, 2017 |
| 6 |
Efficient subset selection for the expected opportunity cost
Gao SY, Chen WW
Automatica, 59, 19, 2015 |
| 7 |
Efficient Computing Budget Allocation for Simulation-Based Optimization With Stochastic Simulation Time
Jia QS
IEEE Transactions on Automatic Control, 58(2), 539, 2013 |
| 8 |
Budget Allocation for Effective Data Collection in Predicting an Accurate DEA Efficiency Score
Wong WP, Jaruphongsa W, Lee LH
IEEE Transactions on Automatic Control, 56(6), 1235, 2011 |
