Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item Prioritizing Patients: Stochastic Dynamic Programming for Surgery Scheduling and Mass Casualty Incident Triage(2011) Herring, William L.; Herrmann, Jeffrey W; Applied Mathematics and Scientific Computation; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The research presented in this dissertation contributes to the growing literature on applications of operations research models to problems in healthcare through the development and analysis of mathematical models for two fundamental problems facing nearly all hospitals: the single-day surgery scheduling problem and planning for triage in the event of a mass casualty incident. Both of these problems can be understood as sequential decision-making processes aimed at prioritizing between different classes of patients under significant uncertainty and are modeled using stochastic dynamic programming. Our study of the single-day surgery scheduling problem represents the first model to capture the sequential nature of the operating room (OR) manager's decisions during the transition between the generality of cyclical block schedules (which allocate OR time to surgical specialties) and the specificity of schedules for a particular day (which assign individual patients to specific ORs). A case study of the scheduling system at the University of Maryland Medical Center highlights the importance of the decision to release unused blocks of OR time and use them to schedule cases from the surgical request queue (RQ). Our results indicate that high quality block release and RQ decisions can be made using threshold-based policies that preserve a specific amount of OR time for late-arriving demand from the specialties on the block schedule. The development of mass casualty incident (MCI) response plans has become a priority for hospitals, and especially emergency departments and trauma centers, in recent years. Central to all MCI response plans is the triage process, which sorts casualties into different categories in order to facilitate the identification and prioritization of those who should receive immediate treatment. Our research relates MCI triage to the problem of scheduling impatient jobs in a clearing system and extends earlier research by incorporating the important trauma principle that patients' long-term (post-treatment) survival probabilities deteriorate the longer they wait for treatment. Our results indicate that the consideration of deteriorating survival probabilities during MCI triage decisions, in addition to previously studied patient characteristics and overall patient volume, increases the total number of expected survivors.Item The Economics of Nuclear Power(2006-11-28) Horst, Ronald L; Rust, John; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)We extend economic analysis of the nuclear power industry by developing and employing three tools. They are 1) compilation and unification of operating and accounting data sets for plants and sites, 2) an abstract industry model with major economic agents and features, and 3) a model of nuclear power plant operators. We build a matched data set to combine dissimilar but mutually dependent bodies of information. We match detailed information on the activities and conditions of individual plants to slightly more aggregated financial data. Others have exploited the data separately, but we extend the sets and pool available data sets. The data reveal dramatic changes in the industry over the past thirty years. The 1980s proved unprofitable for the industry. This is evident both in the cost data and in the operator activity data. Productivity then improved dramatically while cost growth stabilized to the point of industry profitability. Relative electricity prices may be rising after nearly two decades of decline. Such demand side trends, together with supply side improvements, suggest a healthy industry. Our microeconomic model of nuclear power plant operators employs a forward-looking component to capture the information set available to decision makers and to model the decision-making process. Our model includes features often overlooked elsewhere, including electricity price equations and liability. Failure to account for changes in electricity price trends perhaps misled earlier scholars, and they attributed to other causes the effects on profits of changing price structures. The model includes potential losses resulting from catastrophic nuclear accidents. Applications include historical simulations and forecasts. Nuclear power involves risk, and accident costs are borne both by plant owners and the public. Authorities regulate the industry and balance conflicting desires for economic gain and safety. We construct an extensible model with regulators, plant operators, insurance companies, and consumers. The model possesses key attributes of the industry seldom found in combination elsewhere. We then add additional details to make the model truer to reality. The work extends and corrects existing literature on the definition, effects, and magnitudes of implicit subsidies resulting from liability limits.Item INTEGRATED PRODUCTION-DISTRIBUTION SCHEDULING IN SUPPLY CHAINS(2005-05-09) Pundoor, Guruprasad; Chen, Zhi-Long; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)We consider scheduling issues in different configurations of supply chains. The primary focus is to integrate production and distribution activities in the supply chain in order to optimize the tradeoff between total cost and service performance. The cost may be based on actual expenses such as the expense incurred during the distribution phase, and service performance can be expressed in terms of time based performance measures such as completion times and tardiness. Our goal is to achieve the following objectives: (i) To propose various integrated production-distribution scheduling models that closely mirror practical supply chain operations in some environments. (ii) To develop computationally effective optimization based solution algorithms to solve these models. (iii) To provide managerial insights into the potential benefits of coordination between production and distribution operations in a supply chain. We analyze four different configurations of supply chains. In the first model, we consider a setup with multiple manufacturing plants owned by the same firm. The manufacturer receives a set of distinct orders from the retailers before a selling season, and needs to determine the order assignment, production schedule, and distribution schedule so as to optimize a certain performance measure of the supply chain. The second model deals with a supply chain consisting of one supplier and one or more customers, where the customers set due dates on the orders they place. The supplier has to come up with an integrated production-distribution schedule that optimizes the tradeoff between maximum tardiness and total distribution cost. In the third model, we study an integrated production and distribution scheduling model in a two-stage supply chain consisting of one or more suppliers, a warehouse, and a customer. The objective is to find jointly a cyclic production schedule at each supplier, a cyclic delivery schedule from each supplier to the warehouse, and a cyclic delivery schedule from the warehouse to the customer so that the customer demand for each product is satisfied fully at minimum total production, inventory and distribution cost. In the fourth model, we consider a system with one supplier and one customer with a set of orders placed at the beginning of the planning horizon. Unlike the earlier models, here each order can have a different size. Since the shipping capacity per batch is finite, we have to solve an integrated production-distribution scheduling and order-packing problem. Our objective is to minimize the number of delivery batches subject to certain service performance measures such as the average lead time or compliance with deadlines for the orders.Item Time Inconsistency in the Credit Card Market(2004-11-29) shui, haiyan; Ausubel, Lawrence M; Rust, John; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Does consumer behavior exhibit time inconsistency? This is an essential, yet difficult question to answer. This dissertation attempts to answer this question based on a large-scale randomized experiment in the credit card market. Specifically, we apply both time consistent preferences (exponential) and time inconsistent preferences (hyperbolic) to study two puzzling phenomena in the experiment. The two puzzling phenomena seem to suggest time inconsistency in consumer behavior. First, more consumers accept an introductory offer that has a lower interest rate with a shorter duration than a higher interest rate and a longer duration. However, ex post borrowing behavior reveals that the longer duration offer is better, because respondents keep on borrowing on the credit card after the introductory period. Second, consumers are reluctant to switch, and many of those consumers who have switched before fail to switch again later. A multi-period model with complete information is studied analytically, which shows that standard exponential preferences cannot explain the observed behavior because they are time consistent. However, hyperbolic preferences that are time inconsistent come closer to rationalizing the observed behavior. In particular, two special cases of hyperbolic discounting are carefully examined, sophisticated and naive. Sophisticated consumers prefer the short offer because it serves as a self-commitment device. Naive consumers prefer the short offer because they underestimate their future debt. To further explore the possibility of explaining observed behavior by exponential preferences, we study a dynamic model in which realistic random shocks are incorporated. Estimation results show that consumers have severe self-control problem with a present-bias factor (0.8). It is also shown that the average switching cost is $150. With the estimated parameters, the dynamic model can replicate quantitative features of the data.