Fully sequential procedures for large-scale ranking-and-selection problems in parallel computing environments
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 1177-1194 |
| Journal / Publication | Operations Research |
| Volume | 63 |
| Issue number | 5 |
| Online published | 18 Sep 2015 |
| Publication status | Published - Sep 2015 |
Link(s)
Abstract
Fully sequential ranking-and-selection (RandS) procedures to find the best from a finite set of simulated alternatives are often designed to be implemented on a single processor. However, parallel computing environments, such as multi-core personal computers and many-core servers, are becoming ubiquitous and easily accessible for ordinary users. In this paper, we propose two types of fully sequential procedures that can be used in parallel computing environments. We call them vector-filling procedures and asymptotic parallel selection procedures, respectively. Extensive numerical experiments show that the proposed procedures can take advantage of multiple parallel processors and solve large-scale RandS problems.
Research Area(s)
- Asymptotic validity, Fully sequential procedures, Parallel computing, Statistical issues
Citation Format(s)
Fully sequential procedures for large-scale ranking-and-selection problems in parallel computing environments. / Luo, Jun; Hong, L. Jeff; Nelson, Barry L.; Wu, Yang.
In: Operations Research, Vol. 63, No. 5, 09.2015, p. 1177-1194.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
