Fully sequential selection procedures with control variates

Shing Tsai and Barry Nelson

IISE Transactions, 2010, vol. 42, issue 1, 71-82

Abstract: Fully sequential selection procedures have been developed in the field of stochastic simulation to find the simulated system with the best expected performance when the number of alternatives is finite. Kim and Nelson proposed the procedure to allow for unknown and unequal variances and the use of common random numbers. approximates the raw sum of differences between observations from two systems as a Brownian motion process with drift and uses a triangular continuation region to decide the stopping time of the selection process. In this paper new fully sequential selection procedures are derived that employ a more effective sum of differences, which is called a controlled sum. Two provably valid procedures and an approximate procedure are described. Empirical results and a realistic illustration are provided to compare the efficiency of these procedures with other procedures that solve the same problem.[Supplemental materials are available for this article. Go to the publisher's online edition of IIE Transactions for the following supplemental resources: Proofs and guidelines to choose appropriate parameters.]

Date: 2010
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://hdl.handle.net/10.1080/07408170903228942 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:uiiexx:v:42:y:2010:i:1:p:71-82

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/uiie20

DOI: 10.1080/07408170903228942

Access Statistics for this article

IISE Transactions is currently edited by Jianjun Shi

More articles in IISE Transactions from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().