A comparison between the OCBA and the KN selection procedures for maximizing the probability of correct selection
-
Published:2023-03-25
Issue:
Volume:
Page:
-
ISSN:1793-9623
-
Container-title:International Journal of Modeling, Simulation, and Scientific Computing
-
language:en
-
Short-container-title:Int. J. Model. Simul. Sci. Comput.
Author:
Alrefaei Mahmoud H.1ORCID,
Salhiyeh Dina A.1
Affiliation:
1. Department of Mathematics and Statistics, Jordan University of Science and Technology, Irbid 22110, Jordan
Abstract
Selecting a system or a subset of systems that have the best performance among many alternative systems is an important area of research. All efforts are paid to do this selection with a high probability of correct selection [Formula: see text]. In this paper, we compare the performance of two popular procedures used to select the best systems, namely, the method of Kim and Nelson [Formula: see text] which is considered as a ranking and selection procedure, and the Optimal Computing Budget Allocation [Formula: see text] procedure. Both of these procedures determine the number of samples for each system that are needed to achieve the maximum [Formula: see text]. Recently, the [Formula: see text] has been developed in order to be able to approximate the value of [Formula: see text], so both procedures approximate the value of [Formula: see text]. To do the comparison, we implement the two methods on two examples; one is a generic example and the other one involves a management of inventory model. The two examples assure that the [Formula: see text] method always outperforms the [Formula: see text] method.
Publisher
World Scientific Pub Co Pte Ltd
Subject
Computer Science Applications,Modeling and Simulation,General Engineering,General Mathematics