Operations Research, Systems Engineering and Industrial Engineering Commons^™

Water Resources Planning Under Deep Uncertainty For Physically, Socially, And Politically Complex Systems, Sarah St. George Freeman

Doctoral Dissertations

Water supply systems, particularly those of large cities, are complex systems linking supply, regulatory and distribution infrastructure, and points of use. Despite their physical complexities, it is infrequent that full supply, distribution, end use, and feedbacks therein are considered in an integrated manner. These complex systems-of-systems face large uncertainties related to physical aspects such as degradation of infrastructure, changing demand, and climate variability and change. Though great, such physical uncertainties often pale in comparison to the those related to the human systems in place to manage them and yet uncertainty in the decision-making landscape is often grossly simplified in our …

Decision-Analytic Models Using Reinforcement Learning To Inform Dynamic Sequential Decisions In Public Policy, Seyedeh Nazanin Khatami

Doctoral Dissertations

We developed decision-analytic models specifically suited for long-term sequential decision-making in the context of large-scale dynamic stochastic systems, focusing on public policy investment decisions. We found that while machine learning and artificial intelligence algorithms provide the most suitable frameworks for such analyses, multiple challenges arise in its successful adaptation. We address three specific challenges in two public sectors, public health and climate policy, through the following three essays. In Essay I, we developed a reinforcement learning (RL) model to identify optimal sequence of testing and retention-in-care interventions to inform the national strategic plan “Ending the HIV Epidemic in the US”. …

Enabling Declarative And Scalable Prescriptive Analytics In Relational Data, Matteo Brucato

Doctoral Dissertations

Constrained optimization problems are at the heart of significant applications in a broad range of domains, including finance, transportation, manufacturing, and healthcare. They are often found at the final step of business analytics, namely prescriptive analytics, to allow businesses to transform a rich understanding of data, typically provided by advanced predictive models, into actionable decisions. Modeling and solving these problems has relied on application-specific solutions, which are often complex, error-prone, and do not generalize. Our goal is to create a domain-independent, declarative approach, supported and powered by the system where the data relevant to these problems typically resides: the database. …

Modeling The Economic And Environmental Performance Of Offshore Wind Energy, Alexana Cranmer

Doctoral Dissertations

Offshore wind is a growing source of energy globally. Like any energy technology, it has impacts on the environment. In the case of renewable energy, we need a way to consider the environmental benefits as well as the environmental costs. This dissertation develops a set of models to examine the economic and environmental costs and benefits and the trade-offs between them. We ask how much offshore wind energy should be sited, and where should that offshore wind energy be located? The first model estimates the economic impact of wake interactions between wind farms. Wind farm sites are chosen through a …

Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan

Masters Theses

Recent advances in cloud-based big-data technologies now makes data driven solutions feasible for increasing numbers of scientific computing applications. One such data driven solution approach is machine learning where patterns in large data sets are brought to the surface by finding complex mathematical relationships within the data. Nowcasting or short-term prediction of rainfall in a given region is an important problem in meteorology. In this thesis we explore the nowcasting problem through a data driven approach by formulating it as a machine learning problem.

State-of-the-art nowcasting systems today are based on numerical models which describe the physical processes leading to …

Stochastic Network Design: Models And Scalable Algorithms, Xiaojian Wu

Doctoral Dissertations

Many natural and social phenomena occur in networks. Examples include the spread of information, ideas, and opinions through a social network, the propagation of an infectious disease among people, and the spread of species within an interconnected habitat network. The ability to modify a phenomenon towards some desired outcomes has widely recognized benefits to our society and the economy. The outcome of a phenomenon is largely determined by the topology or properties of its underlying network. A decision maker can take management actions to modify a network and, therefore, change the outcome of the phenomenon. A management action is an …

X-Band Dual Polarization Phased-Array Radar For Meteorological Applications, Krzysztof Orzel

Doctoral Dissertations

This dissertation details the development and operation of a novel dual-polarized Phase-Tilt Weather Radar (PTWR) designed for meteorological applications. The use of radar has a well-documented history in detection and classification of weather phenomena, but due to the limited mechanical scanning speed, its usage for severe weather observations remains far from ideal. The PTWR utilizes phased-array technology and provides unique capabilities such as smart scanning, fast scan update, and tracking. This technology is considered a candidate for a replacement and consolidation of the current US weather and surveillance radar networks. The dissertation can be divided into three parts. First, the …

Model-Based Guidance For Human-Intensive Processes, Stefan Christov

Doctoral Dissertations

Human-intensive processes (HIPs), such as medical processes involving coordination among doctors, nurses, and other medical staff, often play a critical role in society. Despite considerable work and progress in error reduction, human errors are still a major concern for many HIPs. To address this problem of human errors in HIPs, this thesis investigates two approaches for online process guidance, i.e., for guiding process performers while a process is being executed. Both approaches rely on monitoring a process execution and base the guidance they provide on a detailed formal process model that captures the recommended ways to perform the corresponding HIP. …

Defining, Evaluating, And Improving The Process Of Verifying Patient Identifiers, Junghee Jo

Doctoral Dissertations

Patient identification errors are a major cause of medication errors. During medication administration, failure to identify patients correctly can lead to patients receiving incorrect medications, perhaps resulting in adverse drug events and even death. Most medication error studies to date have focused on reporting patient misidentification statistics from case studies, on classifying types of patient identification errors, or on evaluating the impact of technology on the patient identification process, but few have proposed specific strategies or guidelines to decrease patient identification errors. This thesis aims to improve the verification of patient identifiers (VPI) process by making three key contributions to …

Spatial And Temporal Correlations Of Freeway Link Speeds: An Empirical Study, Piotr J. Rachtan

Masters Theses 1911 - February 2014

Congestion on roadways and high level of uncertainty of traffic conditions are major considerations for trip planning. The purpose of this research is to investigate the characteristics and patterns of spatial and temporal correlations and also to detect other variables that affect correlation in a freeway setting. 5-minute speed aggregates from the Performance Measurement System (PeMS) database are obtained for two directions of an urban freeway – I-10 between Santa Monica and Los Angeles, California. Observations are for all non-holiday weekdays between January 1st and June 30th, 2010. Other variables include traffic flow, ramp locations, number of lanes and the …