Fully sequential procedures for large-scale ranking-and-selection problems in parallel computing environments

Jun Luo, L. Jeff Hong, Barry L. Nelson, Yang Wu

Research output: Contribution to journalArticle

40 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)1177-1194
Number of pages18
JournalOperations Research
Volume63
Issue number5
DOIs
StatePublished - Sep 1 2015

Keywords

  • Asymptotic validity
  • Fully sequential procedures
  • Parallel computing
  • Statistical issues

ASJC Scopus subject areas

  • Computer Science Applications
  • Management Science and Operations Research

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