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 Hong Wan

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Average citations per article6.36
Citation Count178
Publication count28
Publication years1987-2017
Available for download21
Average downloads per article115.14
Downloads (cumulative)2,418
Downloads (12 Months)198
Downloads (6 Weeks)34
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29 results found Export Results: bibtexendnoteacmrefcsv

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1
December 2018 WSC '18: Proceedings of the 2018 Winter Simulation Conference
Publisher: IEEE Press
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 1,   Downloads (12 Months): 1,   Downloads (Overall): 1

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Simulation models are integral to modern scientific research, national defense, industry and manufacturing, and in public policy debates. These models tend to be extremely complex, often with thousands of factors and many sources of uncertainty. To understand the impact of these factors and their interactions on model outcomes requires efficient, ...

2
December 2017 WSC '17: Proceedings of the 2017 Winter Simulation Conference
Publisher: IEEE Press
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 6,   Downloads (12 Months): 14,   Downloads (Overall): 14

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In this paper, we introduce a sequential procedure for the Multi-Objective Ranking and Selection (MOR&S) problems that identifies the Pareto front with a guaranteed probability of correct selection (PCS). In particular, the proposed procedure is fully sequential using the test statistics built upon the generalized sequential probability ratio test (GSPRT). ...

3
December 2016 WSC '16: Proceedings of the 2016 Winter Simulation Conference
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 1,   Downloads (12 Months): 3,   Downloads (Overall): 24

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STRONG is a response surface methodology based algorithm that iteratively constructs linear or quadratic fitness model to guide the searching direction within the trust region. Despite its elegance and convergence, one bottleneck of the original STRONG in high-dimensional problems is the high cost per iteration. This paper proposes a new ...

4
December 2015 WSC '15: Proceedings of the 2015 Winter Simulation Conference
Publisher: IEEE Press
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 2,   Downloads (12 Months): 14,   Downloads (Overall): 15

Full text available: PDFPDF
Simulation models are integral to modern scientific research, national defense, industry and manufacturing, and in public policy debates. These models tend to be extremely complex, often with thousands of factors and many sources of uncertainty. To understand the impact of these factors and their interactions on model outcomes requires efficient, ...

5
December 2014 WSC '14: Proceedings of the 2014 Winter Simulation Conference
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 1,   Downloads (12 Months): 11,   Downloads (Overall): 20

Full text available: PDFPDF
This paper considers the factor screening problem with multiple responses for simulation experiments. The objective is to identify important factors with controlled Family-Wise Error Rate. We assume a multiple-response first-order linear model, the responses follow a multivariate normal distribution, and estimated effect coefficients also follow multivariate normal distribution. Two likelihood ...

6
July 2014 SummerSim '14: Proceedings of the 2014 Summer Simulation Multiconference
Publisher: Society for Computer Simulation International
Bibliometrics:
Citation Count: 5
Downloads (6 Weeks): 3,   Downloads (12 Months): 24,   Downloads (Overall): 104

Full text available: PDFPDF
Simulation models are integral to modern scientific research, national defense, industry and manufacturing, and public policy debates. These models tend to be extremely complex, often with thousands of factors and many sources of uncertainty. To understand the impact these factors and their interactions have on model outcomes requires efficient, high-dimensional ...
Keywords: design of experiments, response surface metamodeling, data farming, robust design

7
December 2013 WSC '13: Proceedings of the 2013 Winter Simulation Conference: Simulation: Making Decisions in a Complex World
Publisher: IEEE Press
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 2,   Downloads (12 Months): 7,   Downloads (Overall): 38

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Screening methods are beneficial for studies involving simulations that have a large number of variables where a relatively small (but unknown) subset is important. In this paper, we show how a newly proposed Lasso-optimal screening design and analysis method can be useful for efficiently conducting simulation screening experiments. Our approach ...

8
April 2013 INFORMS Journal on Computing: Volume 25 Issue 2, Spring 2013
Publisher: INFORMS
Bibliometrics:
Citation Count: 7

Response surface methodology RSM is a widely used method for simulation optimization. Its strategy is to explore small subregions of the decision space in succession instead of attempting to explore the entire decision space in a single attempt. This method is especially suitable for complex stochastic systems where little knowledge ...
Keywords: simulation optimization, trust region method, black-box method, response surface methodology

9
December 2012 WSC '12: Proceedings of the Winter Simulation Conference
Publisher: Winter Simulation Conference
Bibliometrics:
Citation Count: 12
Downloads (6 Weeks): 1,   Downloads (12 Months): 8,   Downloads (Overall): 144

Full text available: PDFPDF
Simulation models are integral to modern scientific research, national defense, industry and manufacturing, and in public policy debates. These models tend to be extremely complex, often with thousands of factors and many sources of uncertainty. To understand the impact of these factors and their interactions on model outcomes requires efficient, ...

10
December 2011 WSC '11: Proceedings of the Winter Simulation Conference
Publisher: Winter Simulation Conference
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 0,   Downloads (12 Months): 0,   Downloads (Overall): 8

Full text available: PDFPDF
Simulation optimization has received a great deal of attention over the decades, which probably can be attributed to its generality and solvability in many practical problems. On the other hand, simulation optimization is well-recognized as a difficult problem, especially when the problem dimensionality grows. STRONG is a newly-developed method built ...

11
December 2011 WSC '11: Proceedings of the Winter Simulation Conference
Publisher: Winter Simulation Conference
Bibliometrics:
Citation Count: 6
Downloads (6 Weeks): 1,   Downloads (12 Months): 16,   Downloads (Overall): 93

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This paper is concerned with production planning in manufacturing, which can be loosely defined as the problem of finding a release plan for jobs that minimizes the total cost (or maximizes the total profit). Production planning is a challenging optimization problem due to the variability in manufacturing systems and uncertainty ...

12
December 2011 WSC '11: Proceedings of the Winter Simulation Conference
Publisher: Winter Simulation Conference
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 0,   Downloads (12 Months): 1,   Downloads (Overall): 25

Full text available: PDFPDF
Recent advances in high-performance computing have pushed computational capabilities to a petaflop (a thousand trillion operations per second) in a single computing cluster. This breakthrough has been hailed as a way to fundamentally change science and engineering by letting people perform experiments that were previously beyond reach. But for those ...

13
July 2010 INFORMS Journal on Computing: Volume 22 Issue 3, Summer 2010
Publisher: INFORMS
Bibliometrics:
Citation Count: 9

Controlled sequential bifurcation (CSB) is a factor-screening method for discrete-event simulations. It combines a multistage hypothesis testing procedure with the original sequential bifurcation procedure to control both the power for detecting important effects at each bifurcation step and the Type I error for each unimportant factor under heterogeneous variance conditions ...
Keywords: analysis, experiment, simulation, statistics

14
December 2009 WSC '09: Winter Simulation Conference
Publisher: Winter Simulation Conference
Bibliometrics:
Citation Count: 11
Downloads (6 Weeks): 11,   Downloads (12 Months): 40,   Downloads (Overall): 258

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This work proposes a new method for approximating the Pareto front of a multi-objective simulation optimization problem (MOP) where the explicit forms of the objective functions are not available. The method iteratively approximates each objective function using a metamodeling scheme and employs a weighted sum method to convert the MOP ...

15
December 2009 WSC '09: Winter Simulation Conference
Publisher: Winter Simulation Conference
Bibliometrics:
Citation Count: 11
Downloads (6 Weeks): 1,   Downloads (12 Months): 8,   Downloads (Overall): 89

Full text available: PDFPDF
Recent advances in high-performance computing have pushed computational capabilities to a petaflop (a thousand trillion operations per second) in a single computing cluster. This breakthrough has been hailed as a way to fundamentally change science and engineering by letting people perform experiments that were previously beyond reach. But for those ...

16
December 2009 WSC '09: Winter Simulation Conference
Publisher: Winter Simulation Conference
Bibliometrics:
Citation Count: 3
Downloads (6 Weeks): 0,   Downloads (12 Months): 0,   Downloads (Overall): 21

Full text available: PDFPDF
Simulation optimization refers to the iterative procedure in search of the optimal parameter when the objective function can only be evaluated by stochastic simulation. STRONG (Stochastic Trust Region Response Surface Convergent Method) is a newly developed design-of-experiments based simulation optimization method. It incorporates the idea of trust region method (TRM) ...

17
September 2009 Computational & Mathematical Organization Theory: Volume 15 Issue 3, September 2009
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 3

Simulation experiments are typically faster, cheaper and more flexible than physical experiments. They are especially useful for pilot studies of complicated systems where little prior knowledge of the system behavior exists. One key characteristic of simulation experiments is the large number of factors and interactions between factors that impact decision ...
Keywords: Hierarchy organizational model, Screening, Design of experiments, Simulation

18 published by ACM
March 2009 ACM Transactions on Modeling and Computer Simulation (TOMACS): Volume 19 Issue 2, March 2009
Publisher: ACM
Bibliometrics:
Citation Count: 11
Downloads (6 Weeks): 1,   Downloads (12 Months): 6,   Downloads (Overall): 350

Full text available: PDFPDF
Analysts examining complex simulation models often conduct screening experiments to identify important factors. The controlled sequential bifurcation screening procedures CSB and CSB-X use a sequence of tests to classify factors as important or unimportant, while controlling Type I error and power. These procedures require analysts to identify the directions of ...
Keywords: Simulation theory, controlled sequential bifurcation, experimentation

19
September 2008 ICIC '08: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

A new variable step-size(VSS) LMS adaptive algorithm based on the convergence ratio of MSE and the correlation between reference signal and output error is proposed in the paper. Theory analyzing and simulation results prove that the new algorithm improves the convergent speed of general LMS algorithm and optimizes the trace ...
Keywords: adaptive filter, variable step, LMS, MSE

20
December 2007 WSC '07: Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Publisher: IEEE Press
Bibliometrics:
Citation Count: 8
Downloads (6 Weeks): 1,   Downloads (12 Months): 13,   Downloads (Overall): 180

Full text available: PDFPDF
Response Surface Methodology (RSM) is a metamodel-based optimization method. Its strategy is to explore small subregions of the parameter space in succession instead of attempting to explore the entire parameter space directly. This method has been widely used in simulation optimization. However, RSM has two significant shortcomings: Firstly, it is ...



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