Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/30462
Title: | Comparison of Kriging-based algorithms for simulation optimization with heterogeneous noise | Authors: | Jalali, H VAN NIEUWENHUYSE, Inneke Picheny, V |
Issue Date: | 2017 | Publisher: | ELSEVIER SCIENCE BV | Source: | EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 261 (1) , p. 279 -301 | Abstract: | In this article we investigate the unconstrained optimization (minimization) of the performance of a system that is modeled through a discrete-event simulation. In recent years, several algorithms have been proposed which extend the traditional Kriging-based simulation optimization algorithms (assuming deterministic outputs) to problems with noise. Our objective in this paper is to compare the relative performance of a number of these algorithms on a set of well-known analytical test functions, assuming different patterns of heterogeneous noise. We also apply the algorithms to a popular inventory test problem. The conclusions and insights obtained may serve as a useful guideline for researchers aiming to apply Kriging-based algorithms to solve engineering and/or business problems, and may be useful in the development of future algorithms. (C) 2017 Elsevier B.V. All rights reserved. | Keywords: | Simulation;Stochastic Kriging;Heterogeneous noise;Ranking and selection;Optimization via simulation | Document URI: | http://hdl.handle.net/1942/30462 | ISSN: | 0377-2217 | e-ISSN: | 1872-6860 | DOI: | 10.1016/j.ejor.2017.01.035 | ISI #: | WOS:000400221000023 | Rights: | 2017 Elsevier B.V. All rights reserved. | Category: | A1 | Type: | Journal Contribution |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
1-s2.0-S037722171730070X-main.pdf Restricted Access | Published version | 3.38 MB | Adobe PDF | View/Open Request a copy |
SCOPUSTM
Citations
25
checked on Sep 7, 2020
WEB OF SCIENCETM
Citations
57
checked on Sep 28, 2024
Page view(s)
64
checked on Sep 7, 2022
Download(s)
4
checked on Sep 7, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.