An optimal opportunity cost selection procedure for a fixed number of designs

Siyang Gao; Leyuan Shi

doi:10.1109/WSC.2014.7020220

An optimal opportunity cost selection procedure for a fixed number of designs

Siyang Gao
, Leyuan Shi

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

4 Citations (Scopus)

Abstract

The expected opportunity cost is an important quality measure for the selection for the best simulated design among a set of design alternatives. It takes the case of incorrect selection into consideration and is particularly useful for risk-neutral decision makers. In this paper, we characterize the optimal selection rule which minimizes the expected opportunity cost by controlling the number of simulation replications allocated to each design. The observation noise of each design is allowed to have a general distribution. A comparison with other selection procedures in the numerical experiments shows the higher efficiency of the proposed method.

Original language	English
Title of host publication	Proceedings - Winter Simulation Conference
Publisher	IEEE
Pages	3952-3958
Volume	2015-January
ISBN (Print)	9781479974863
DOIs	https://doi.org/10.1109/WSC.2014.7020220
Publication status	Published - 23 Jan 2015
Externally published	Yes
Event	2014 Winter Simulation Conference, WSC 2014 - Savannah, United States Duration: 7 Dec 2014 → 10 Dec 2014 http://www.wintersim.org/2014/

Publication series

Name
Volume	2015-January
ISSN (Print)	0891-7736

Conference

Conference	2014 Winter Simulation Conference, WSC 2014
Place	United States
City	Savannah
Period	7/12/14 → 10/12/14
Internet address	http://www.wintersim.org/2014/

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10.1109/WSC.2014.7020220

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doi = "10.1109/WSC.2014.7020220",

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AU - Shi, Leyuan

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AB - The expected opportunity cost is an important quality measure for the selection for the best simulated design among a set of design alternatives. It takes the case of incorrect selection into consideration and is particularly useful for risk-neutral decision makers. In this paper, we characterize the optimal selection rule which minimizes the expected opportunity cost by controlling the number of simulation replications allocated to each design. The observation noise of each design is allowed to have a general distribution. A comparison with other selection procedures in the numerical experiments shows the higher efficiency of the proposed method.

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DO - 10.1109/WSC.2014.7020220

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781479974863

VL - 2015-January

SP - 3952

EP - 3958

BT - Proceedings - Winter Simulation Conference

PB - IEEE

T2 - 2014 Winter Simulation Conference, WSC 2014

Y2 - 7 December 2014 through 10 December 2014

ER -

An optimal opportunity cost selection procedure for a fixed number of designs

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