Hong Wan

North Carolina State University | NCSU · Department of Industrial & Systems Engineering

Blockchain is an append-only digital database with a decentralized peer-to-peer framework. Motivated by tremendous attention from both academic and industrial communities since the emergence of cryptocurrency, we introduce this novel technology and review its cut-of-edge research related to financial e-services in this chapter. This chapter first d...

As agents interact and influence one another in a social network, the opinions they hold about some common topic can change over time. These changes may enable us to infer mechanisms of the network that control how interactions lead to opinion change. Inferring such mechanisms from opinion data could enable analysis of social influence in data-spar...

enMachine learning and blockchain are two of the most notable technologies of recent years. The first is the foundation of artificial intelligence and big data analysis, and the second has significantly disrupted the financial industry. Both technologies are data-driven, and thus there are rapidly growing interests in integrating both for more secu...

As the first and most famous cryptocurrency-based blockchain technology, Bitcoin has attracted tremendous attention from both academic and industrial communities in the past decade. A Bitcoin network is comprised of two interactive parties: individual miners and mining pool managers, each of which strives to maximize its own utility. In particular,...

Screening experiments are performed to eliminate unimportant factors so that the remaining important factors can be more thoroughly studied in later experiments. Sequential screening methods are specifically fit for simulation experiments. They are usually more efficient than one-step procedures. The challenge is to prove the "correctness" of the r...

Computer simulation is an appealing approach for the reliability analysis of structure-based software systems as it can accommodate important complexities present in realistic systems. When the system is complicated, a screening experiment to quickly identify important factors (components) can significantly improve the efficiency of analysis. The c...

Factor screening is performed to eliminate unimportant factors so that the remaining important factors can be more thoroughly studied in later experiments. Controlled Sequential Bifurcation (CSB) and Controlled Sequential Fac-torial Design (CSFD) are two new screening methods for discrete-event simulations. Both methods use hypothesis testing proce...

This paper proposes two fully sequential procedures for selecting the "best" system with a guaranteed probability of correct selection (PCS). The main features of the proposed procedures include: (1) adopting a Bonferroni-free model that overcomes the conservativeness of the Bonferroni correction and delivers the exact probabilistic guarantee witho...

Blockchain is a distributed, append-only digital ledger (database). The technology has caught much attention since the emergence of cryptocurrency, and there is an increasing number of blockchain applications in a wide variety of businesses. The concept, however, is still novel to many members of the simulation and operations research community. In...

Motivated by the growing interests in Bitcoin blockchain technology, we build a Monte-Carlo simulation model to study the miners' and mining pool managers' decisions in the Bitcoin blockchain network. Our simulation model aims to capture the dynamics of participants of these two different parties and how their decisions collectively affect the syst...

Machine learning (including deep and reinforcement learning) and blockchain are two of the most noticeable technologies in recent years. The first one is the foundation of artificial intelligence and big data, and the second one has significantly disrupted the financial industry. Both technologies are data-driven, and thus there are rapidly growing...

The state‐of‐the‐art triboelectric nanogenerators (TENGs) are constructed with synthetic polymers, curtailing their application prospects and relevance in sustainable technologies. The economically viable transformation and engineering of naturally abundant materials into efficient TENGs for mechanical energy harvesting is meaningful not only for f...

Preventable readmissions are a large and growing concern throughout healthcare in the United States, representing as many as 20% of all hospitalizations (30-day post-discharge) and an estimated $17 to $26 billion in unnecessary costs annually. National quality initiatives and Medicare reimbursement financial incentives have stimulated significant e...

In a produce-to-order environment, it is of substantial interest to be able to quote a tight and reliable lead time for a new job (or order) upon its arrival to a manufacturing system. This work developed a simulation-based statistical approach to provide responsive and high-quality prediction of a new job's flow time through the system, which rend...

Simulation optimization has received a great deal of attention over the decades due 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. Stochastic Trust-Region Response Surface Method (STRONG) is a newly...

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, hi...

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 us...

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 is available. A...

This article studies a firm that procures a product from a supplier. The quality of each product unit is measured by a continuous variable that follows a normal distribution and is correlated within a batch. The firm conducts an inspection and pays the supplier only if the product batch passes the inspection. The inspection not only serves the purp...

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, h...

The detection of radioactive materials has become a critical issue for environmental services, public health, and national security. This paper proposes a spatial statistical method to detect and localize a hidden radioactive source. Based on a detection system of multiple radiation detectors, the statistical model assumes that the counts of radiat...

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 bui...

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 in future demand, b...

This paper presents a comprehensive framework for the strategic capacity expansion of production equipment in semiconductor manufacturing, and the proposed approach is applied to a model of an actual wafer fabrication facility. It is the intention of this work to show that, once intelligently integrated, an analytical queueing model and a numeric c...

The coset pattern matrix contains more detailed information about effect aliasing in a factorial design than the commonly used wordlength pattern. More flexible and elaborate design criteria can be proposed using the coset pattern matrix. We establish an identity that relates the coset pattern matrix of a design to that of its complement. As an app...

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 hetero...

A cumulative sum (CUSUM) control chart is one of the most popular methods used to detect a process mean shift. When one specific size of the mean shift is assumed, the CUSUM chart can be optimally designed in terms of average run length (ARL). In practice, however, the size of the mean shift is usually unknown, and the CUSUM chart can perform poorl...

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 thos...

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 trus...

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 into a set o...

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 thos...

Screening experiments are performed to eliminate unimportant factors efficiently so that the remaining important factors can be studied more thoroughly in later experiments. This paper proposes controlled sequential factorial design (CSFD) for discrete-event simulation experiments. It combines a sequential hypothesis testing procedure with a tradit...

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...

Analysts examining complex simulation models often con-duct screening experiments to identify the most important factors. Controlled sequential bifurcation (CSB) is a screen-ing procedure, developed specifically for simulation exper-iments, that uses a sequence of hypothesis tests to classify the factors as either important or unimportant. CSB con-...

Condition monitoring uses sensory signals to assess the health of engineering systems. A degradation model is a mathematical characterization of the evolution of a condition signal. Our recent research focuses on using degradation models to compute residual-life distributions for degrading components. Residual-life distributions are important for p...

Factor screening is performed to eliminate unimportant factors so that the remaining important factors can be more thoroughly studied in later experiments. Controlled sequential bifurcation (CSB) and controlled sequential factorial design (CSFD) are two new screening methods for discrete-event simulations. Both methods use hypothesis testing proced...

Armed forces around the world are considering radical transformations to their structures and strategies because of the information revolution and the changing global environment. Senior leadership continually face decisions on how best to structure, modernize, organize, and employ forces in an increasingly uncertain future. For many of these probl...

This note studies the optimal inspection policies in a supply chain in which a manufacturer purchases components from a supplier but has no direct control of component quality. The manufacturer uses an inspection policy and a damage cost sharing contract to encourage the supplier to improve the component quality. We find that all-or-none inspection...

Computer simulation is an appealing approach for the reliability analysis of structure-based software systems as it can accommodate important complexities present in realistic systems. When the system is complicated, a screening experiment to quickly identify important factors (components) can significantly improve the efficiency of analysis. The c...

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 i...

Many outpatient clinics are experimenting with open access scheduling. Under open access, patients see their physicians within a day or two of making their appointment request, and long-term patient booking is very limited. The hope is that these short appointment lead times will improve patient access and reduce uncertainty in clinic operations by...

Factor screening with statistical control makes sense in the context of simulation experiments that have random error, but can be run automatically on a computer and thus can accommodate a large number of replications. The discrete-event simulations common in the operations research field are well suited to controlled screening. In this paper, two...

Screening experiments are performed to eliminate unimportant factors so that the remaining important factors can be more thoroughly studied in later experiments. Sequential bifurcation (SB) is a recent screening method that is well suited for simulation experiments; the challenge is to prove the "correctness" of the results. This paper proposes con...

Factor screening with statistical control makes sense in the context of simulation experiments that have random error, but can be run automatically on a computer and thus can accommodate a large number of replications. The discrete-event simulations common in the operations research field are well suited to controlled screening. In this paper two m...

Analysts examining complex simulation models often conduct screening experiments to identify the most important factors. Controlled sequential bifurcation (CSB) is a screening procedure, developed specifically for simulation experiments, that uses a sequence of hypothesis tests to classify the factors as either important or unimportant. CSB control...

High patient non-attendance rates cause critical problems for many outpatient clinics in the United States. For historical patient attendance data in a primary care clinic, six categorical factors are analyzed in this paper: appointment type, session, patient attendance history, insurance, age group and weather. The main effects of session, insuran...

Screening experiments are performed to eliminate unimportant factors so that the remaining important factors can be more thoroughly studied in later experiments. Sequential bifurcation (SB) is a screening method that is well suited for simulation experiments; the challenge is to prove the "correctness" of the results. This paper proposes controlled...

Screening experiments are performed to eliminate unimportant factors so that the remaining important factors can be more thoroughly studied in later experiments. Sequential bifurcation (SB) is a screening method that is well suited for simulation experiments; the challenge is to prove the "correctness" of the results. This paper proposes Controlled...

Screening experiments are performed to eliminate unimportant factors so that the remaining important factors can be more thoroughly studied in later experiments. Sequential bifurcation (SB) is a screening method that is well suited for simulation experiments; the challenge is to prove the "correctness" of the results. This paper proposes Controlled...

Controlled Sequential Bifurcation (CSB) is a factor-screening method for discrete-event sim- ulations. CSB controls the power for detecting important efiects at each bifurcation step and the Type I Error for each unimportant factor under heterogeneous variance conditions when a main-efiects model applies. Unfortunately, when factors interact|as the...

TRB’s Transit Cooperative Research Program (TCRP) Report 98: Resource Requirements for Demand-Responsive Transportation Services documents a methodology for determining the resources required (i.e., vehicles and vehicle service hours) to provide demand-responsive transportation (DRT) for different levels of demand and different levels of service in...