Fully Sequential Procedures for Large-Scale Ranking-and-Selection Problems in Parallel Computing Environments

被引:70
|
作者
Luo, Jun [1 ]
Hong, L. Jeff [2 ,3 ]
Nelson, Barry L. [4 ]
Wu, Yang [5 ]
机构
[1] Shanghai Jiao Tong Univ, Antai Coll Econ & Management, Shanghai 200052, Peoples R China
[2] City Univ Hong Kong, Coll Business, Dept Econ & Finance, Kowloon, Hong Kong, Peoples R China
[3] City Univ Hong Kong, Coll Business, Dept Management Sci, Kowloon, Hong Kong, Peoples R China
[4] Northwestern Univ, Dept Ind Engn & Management Sci, Evanston, IL 60208 USA
[5] Tmall Co, Hangzhou 310000, Zhejiang, Peoples R China
关键词
fully sequential procedures; parallel computing; statistical issues; asymptotic validity; SIMULATED SYSTEM; 2-STAGE;
D O I
10.1287/opre.2015.1413
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Fully sequential ranking-and-selection (R&S) 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 R&S problems.
引用
收藏
页码:1177 / 1194
页数:18
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