In this paper, we consider the ranking and selection problem of selecting the optimal subset from a finite set of alternative designs.
Abstract—In this paper, we consider the ranking and se- lection problem of selecting the optimal subset from a finite set of alternative designs.
Request PDF | On Aug 1, 2019, Fei Gao and others published Selecting an Optimal Subset with Regression Metamodels * | Find, read and cite all the research ...
Given the total simulation budget constraint, we aim to maximize the probability of correctly selecting the top-m designs. In order to further improve the ...
This research considers the ranking and selection (R&S) problem of selecting the optimal subset from a finite set of alternative designs.
May 1, 2023 · You can solve the problem exactly via a branch-and-bound algorithm known as "leaps and bounds": Furnival, George M., and Robert W. Wilson.
Apr 24, 2019 · In order to improve the selection efficiency, we incorporate the information from across the domain into regression metamodels. In this research ...
May 11, 2022 · I am conducting research on efficient algorithms for finding the best subset of variables for fitting a regression model and I am currently gathering sources, ...
Missing: Optimal Metamodels*.
This research considers the ranking and selection (R&S) problem of selecting the optimal subset from a finite set of alternative designs.
Stepwise regression and Best Subsets regression are common automatic variable selection methods. Learn how they work and which one provides better results.
Missing: Optimal Metamodels*.