Human and freshwater ecosystems are intrinsically interconnected. To better design effective policies, modeling tools and valuation methods are necessary to help understanding the complex reciprocal linkages between ecosystem processes and human actions, and coupled human and natural systems (CNHS) sets up a critical paradigm to do so. It is thus of both academic and empirical appeal to integrate reliable economic valuation methods with tools and models from multiple disciplines in order to quantify the feedbacks between human and natural systems and to inform better policy design. Using freshwater resources as an example, this dissertation contains three essays which integrate natural science and economics models to understand how changes in human behavior and societal policies lead to changes in ecosystem services, and how changes in ecosystem services, in return, affect human decisions. The first two essays focus on agricultural nonpoint source pollution problems in United States and examines the impacts of potential water polices on both water polluters and water demanders. Specifically, in the first essay, a novel coupling between an ecological model of within-lake hydrodynamics and an economic model of hedonic property prices has been developed to quantify the connections between nutrient loading, lake water quality, and economic outcomes. Linking ecological processes with human decision-making provides a basis for enhanced evidence-based decision making in the context of reducing nonpoint-source pollution. In the second essay, an economic mathematical programming model is coupled with an agro-ecosystem model to investigate the behavioral adjustments and environmental pollution outcomes of water quality policies. A complete quantification of costs from all regulating sources are necessary to help pinpoint the efficient water policy design and reflecting the connection between human decisions and ecosystem processes. The third essay focus on the water quantity problem in another developed country, Australia. A discrete choice experiment method has been explored and used to provide estimates of willingness to pay for purchasing irrigation rights to restore a Ramsar-convention wetland. Water policy scenario described in this essay could directly affect the feedback between human and ecosystem processes and serve as a baseline for future planning and policy designs. By offering both conceptual and methodological advancements, this dissertation aims to improve the understanding of coupled human and natural systems and the implementation of water policies. This dissertation also provides a framework to establish multi-disciplinary dialogues and cooperation between scientists and economists in the search of efficient water polices. / Doctor of Philosophy / Freshwater resources are one of the most important elements in our daily life. It provides important goods and services to our society, but at the same time, due to human behaviors, freshwater resources are under threat in both their quality and quantity. This dissertation contains three essays which integrate knowledge from multiple disciplines to help understand and quantify the linkages between human and freshwater resources, and provides information to come up with better water polices. In the first essay, I explore the connections between nutrient loading, lake water quality, and the economic outcomes. The essay illustrates how potential change in nutrient loadings affect lake water quality, and how that induces people’s housing purchase behavior, property sales price and local governments’ property tax revenue. In the second essay, I focus on the agricultural production problem, which is one of the largest source for water quality degradation. By exploring the impacts of water policy on farmers’ production decisions, the essay sheds light on how to better design water polices to maintain farmers’ profit while simultaneously alleviating the impact of agricultural production to water qualities. In the third essay, I utilize a survey method, choice experiments, to elicit people’s willingness to pay for wetland ecosystem health. This could better allocate water resources between agricultural production use and residential use and come up with better water quantity polices.

Yes / Over the past few decades, the banking sectors in Latin America have undergone rapid structural changes to improve the efficiency and resilience of their financial systems. The up-to-date literature shows that all the research studies conducted to analyze the above-mentioned efficiency are based on a deterministic data envelopment analysis (DEA) model or econometric frontier approach. Nevertheless, the deterministic DEA model suffers from a possible lack of statistical power, especially in a small sample. As such, the current research paper develops the technique of satisficing DEA to examine the still less explored case of Peru. We propose a Satisficing DEA model applied to 14 banks operating in Peru to evaluate the bank-level efficiency under a stochastic environment, which is free from any theoretical distributional assumption. The proposed model does not only report the bank efficiency, but also proposes a new framework for peer mining based on the Bayesian analysis and potential improvements with the bias-corrected and accelerated confidence interval. Our study is the first of its kind in the literature to perform a peer analysis based on a probabilistic approach.

The semiconductor industry provides a host of very challenging problems in production planning and scheduling because of the unique features of the wafer fab. This research addresses the need to develop an approach, which can be used to generate optimal or near-optimal solutions to the scheduling problem of a wafer fab, by using Mathematical Programming for a general case of a wafer fab. The problem is approached in two steps. First, the number of lots of different products to be released into the system during each planning period is determined, such that the total tardiness of the product orders is minimized over the planning horizon. Second, the schedule of these lots is determined so that the cycle time of each lot released into the system is minimized. Thus, the performance measures based both on due dates and cycle time are considered. The lot release, tardiness problem is formulated as an integer linear program, and a 3-phase procedure, which utilizes a variation of the Wilkerson-Irwin algorithm, is developed. The performance of this 3-phase procedure is further improved by using insights from classical scheduling theory. The scheduling problem is formulated as a 0-1 integer linear program. An algorithm is developed for tightening the LP relaxation of this 0-1 integer linear programming model (of the scheduling problem) leading to a better performance of the branch and bound procedure used for its solution. Lagrangian relaxation is applied on a carefully chosen set of constraints in the scheduling problem, and a Lagrangian heuristic is developed for scheduling the jobs in each period of the planning horizon. Several useful insights are developed throughout to further improve the performance of the proposed algorithm. Experiments are conducted for both the tardiness and the scheduling problems. Five experiments are conducted for the tardiness problem. Each experiment has a different combination of number of products, machines, and work orders in a small sized wafer fab (2 to 6 products, 8 to 10 station families, 15 to 30 workstations, 9 to19 work orders, and 100 to 250 lots per work order). The solutions obtained by the 3-phase procedure are compared to the optimal solutions of the corresponding tardiness problems, and the tardiness per work order for the 3-phase procedure is 0% to 25% greater than the optimal solution. But the time required to obtain the optimal solution is 22 to 1074 times greater than the time required to obtain the solution through the 3-phase procedure. Thus, the 3-phase procedure can generate almost optimal solutions and requires much smaller computation time than that required by the optimal solution. Four experiments are conducted to test the performance of the scheduling problem. Each experiment has a different combination of number of products, machines, routes, bottleneck stations, processing times, and product mix entering the system each day in a small sized wafer fab (2 products, 8 station families, 18 workstations, and 8 to 10 lots released per day into the system). The solution quality of the schedule generated by the Lagrangian heuristic is compared to the solution provided by the standard dispatching rules available in practice. In each experiment, the cycle time of a product for each dispatching rule is divided by the best cycle time for that product over all the dispatching rules in that experiment. This ratio for the Lagrangian heuristic in each experiment and over all the experiments varies from 100% to 104%. For the standard dispatching rules, this ratio ranges from 100% to 120% in each experiment and also over all the experiments. The average of the ratio over all the experiments is the least for the Lagrangian heuristic. This indicates that for the experiments conducted, the Lagrangian heuristic consistently provides a solution that is, or is close to, the best solution and, hence, quite competitive when compared to the standard dispatching rules. / Master of Science

Approved for public release, distribution is unlimited / Many potential adversaries seek, or already have theater ballistic missiles capable of threatening targets of interest to the United States. The U.S. Missile Defense Agency and armed forces are developing and fielding missile interceptors carried by many different platforms, including ships, aircraft, and ground units. Given some exigent threat, the U.S. must decide where to position defensive platforms and how they should engage potential belligerent missile attacks. To plan such defenses, the Navy uses its Area Air Defense Commander (AADC) system afloat and ashore, the Air Force has its Theater Battle Management Core Systems (TBMCS) used in air operations centers, and the Missile Defense Agency uses the Commander's Analysis and Planning Simulation (CAPS). AADC uses a server farm to exhaustively enumerate potential enemy launch points, missiles, threatened targets, and interceptor platform positions. TBMCS automates a heuristic cookie-cutter overlay of potential launch fans by defensive interceptor envelopes. Given a complete missile attack plan and a responding defense, CAPS assesses the engagement geometry and resulting coverage against manually prepared attack scenarios and defense designs. We express the enemy courses of action as a mathematical optimization to maximize expected damage, and then show how to optimize our defensive interceptor pre-positioning to minimize the maximum achievable expected damage. We can evaluate exchanges where each of our defending platform locations and interceptor commitments are hidden from, or known in advance by the attacker. Using a laptop computer we can produce a provably optimal defensive plan in minutes. / Lieutenant, United States Navy

New European energy policies have set a goal of a high share of renewable energy in electricity markets. In the presence of high levels of renewable generation, and especially wind, there is more uncertainty in the supply. It is natural, that volatility in energy production induces the volatility in energy prices. This can create incentives for the generators to exercise market power by traditional means: withholding the output by conventional generators, bidding not the true marginal costs, or using locational market power. In addition, a new type of market power has been recently observed: exercise of market power on ramp rate. This dissertation focuses on modeling the exercise of market power in power systems with high penetration of wind power. The models consider a single, or multiple profit-maximizing generators. Flexibility is identified as one of the major issues in wind-integrated power systems. Therefore, part of the research studies the behavior of strategic hydropower producers as main providers of flexibility in systems, where hydropower is available.Developed models are formulated as mathematical and equilibrium problems with equilibrium constraints (MPECs and EPECs). The models are recast as mixed-integer linear programs (MILPs) using discretization. Resulting MILPs can be solved directly by commercially-available MILP solvers, or by applying decomposition. Proposed Modified Benders Decomposition Algorithm (MBDA) significantly improves the computational efficiency. / <p>QC 20170516</p>

This thesis develops efficient optimization methods for Model Predictive Control (MPC) to enable its application to constrained systems with fast and uncertain dynamics. The key contribution is an active set method which exploits the parametric nature of the sequential optimization problem and is obtained from a dynamic programming formulation of the MPC problem. This method is first applied to the nominal linear MPC problem and is successively extended to linear systems with additive uncertainty and input constraints or state/input constraints. The thesis discusses both offline (projection-based) and online (active set) methods for the solution of controllability problems for linear systems with additive uncertainty. The active set method uses first-order necessary conditions for optimality to construct parametric programming regions for a particular given active set locally along a line of search in the space of feasible initial conditions. Along this line of search the homotopy of optimal solutions is exploited: a known solution at some given plant state is continuously deformed into the solution at the actual measured current plant state by performing the required active set changes whenever a boundary of a parametric programming region is crossed during the line search operation. The sequence of solutions for the finite horizon optimal control problem is therefore obtained locally for the given plant state. This method overcomes the main limitation of parametric programming methods that have been applied in the MPC context which usually require the offline precomputation of all possible regions. In contrast to this the proposed approach is an online method with very low computational demands which efficiently exploits the parametric nature of the solution and returns exact local DP solutions. The final chapter of this thesis discusses an application of robust tube-based MPC to the nonlinear MPC problem based on successive linearization.

Power system transmission is undergoing rapid changes by the advent of renewable resources of energy, distributed generation, market integration, etc. Transmission planning is, nowadays, about building more inter-connections between adjacent regions or connecting off-shore wind farms to the grid or augmenting the network to support new path flows of energy and is still almost entirely the responsibility of regulated transmission system operator (TSO). Moreover, a well-developed transmission planning includes anticipating the generation investment decisions made by profit-maximizing generation companies (Gencos). Ensuring sustainable development of the power system necessitates coordination between TSO transmission investment with Gencos generation investments. Moreover, coordination between inter-connected TSOs in planning the network is also required in order to hunter the economic benefits of a robust and efficiently planned multi-area power system. Driven by the need for more coordination of the long-term planning of the inter-connected power systems, this thesis aims to develop models to be used in analysis of the multi-TSO multi-Genco transmission and generation planning and suggest mechanisms and coordination approaches for the better functioning of the power system. This includes mathematical models for transmission planning in the context of multiple TSOs and generation-transmission investment planning based on the game theory concepts in applied mathematics and evaluating mechanisms and approaches. / <p>QC 20161110</p>

At the turn of the years 2009 and 2010 the structure of supply chain of the company operating in the Czech and Slovak republic has changed through Warehouse Change Project. The goal of this diploma thesis is to evaluate changes caused by this project in term of mathematical modeling and multi-criterial decision making; eventually, propose appropriate changes in the logistic system.

O planejamento tático da produção é importante para as organizações pois permite um correto dimensionamento dos recursos produtivos, para garantir um atendimento adequado da demanda, e influencia nas decisões de produção em médio prazo buscando soluções que colaborem positivamente no resultado operacional. O objetivo deste trabalho é o desenvolvimento de um modelo de planejamento agregado da produção para aplicação na indústria da carne suína que contemple simultaneamente as atividades finais da produção agropecuária e o ambiente de produção da indústria frigorífica. O modelo proposto contempla um sistema produtivo em dois estágios onde o primeiro estágio apresenta um fluxo divergente de produção envolvendo coprodução e o segundo estágio consiste em uma linha de montagem. O sistema apresentado é composto por uma sequência de rotinas de programação, utilizadas para a geração dos dados de entrada e um modelo matemático baseado em programação linear inteira mista cuja função objetivo é maximizar a margem global. As rotinas para geração de dados de entradas foram programadas em Visual Basic For Application e chamadas de Programa de Geração de Padrões. O modelo de programação matemática foi implementado no software LINGO e suas interfaces com as planilhas do Microsoft Excel. A aplicação do modelo para verificação utilizou dados adaptados de uma empresa envolvida no setor e os resultados obtidos permitiram testar a consistência do modelo para a situação específica. A análise dos resultados demonstrou que o modelo gera soluções que estão alinhadas com os objetivos da organização e responde adequadamente a variações nos dados de entrada. / The tactical planning activities are very important for an organization since it allows an anticipated administration of production resources in order to meet the demand and also because it suggests medium term production decisions that can contribute positively to the operational results of the company. This work aims to develop an aggregate production planning model for the pork industry which takes into consideration factors in the meat processing plant as well as in the final step of farming activities. The presented model approaches a two stage production system where the first stage is characterized by a divergent production flow involving coproduction and the second stange is an assemblage line. The entire system is composed by a sequence of routines used to generate some parameters and a mathematical formulation based on mixed integer linear programming in which the objective function aims to maximize the global margin of the organization. The routines used to generate the parameters where implemented in Visual Basic for Application and were called Pattern Generation Program and the mathematic programming were implemented in LINGO and its interfaces with worksheets of Microsoft Excel. The verification of the model used adapted data from a real company in this industry and could test its consistency for this specific situation. The analyzed results demonstrated that the model generates good solution that contribute to the global objective of the company and the model results response to the changes in the parameter as expected.

Sistemas dutoviários desempenham um papel fundamental na cadeia de suprimento da indústria de petróleo. Este tipo de sistema é responsável pelo transporte da maior parte do volume de petróleo e seus derivados. Sistemas de dutos transportam uma grande quantidade de diferentes tipos de petróleo e seus derivados a custo mais baixo que outros tipos de modais. Dutos interligam campos de produção de petróleo, portos, refinarias, centros de distribuição (ou depósitos), e mercado consumidor. O problema estudado neste trabalho é baseado em um sistema que é composto por uma refinaria que pode transferir vários produtos para um terminal (depósito) através de um único duto. Os produtos são conjuntos de derivados de petróleo que devem ser transferidos da refinaria para o terminal ou do terminal para a refinaria. Ambos, refinaria e terminal estão conectados a outras refinarias, terminais e mercados consumidores e com isto formam uma complexa rede de dutos. Por outro lado há um conjunto de demandas externas e internas. Esta última demanda decorre da necessidade de processamento de produtos intermediários que são misturas compostas de várias correntes intermediárias, tais como diluentes de óleos combustíveis, propano intermediário, e diesel intermediário. Com o objetivo de obter vantagens sobre a estrutura da rede de transporte, torna-se benéfica e mesmo necessária a operação do duto em ambas as direções para atender tanto à demanda externa quanto à interna. O objetivo deste trabalho é desenvolver um modelo matemático para a programação de um sistema de poliduto. A formulação para a programação deve considerar a possibilidade de trocar o sentido do poliduto. Neste contexto, a programação de um poliduto envolve decisões tais como sentido de operação, quantidade, temporização e seqüências de produtos, com objetivo de obter uma solução ótima, considerando todas as restrições de demanda, perfil de produção, estoques e custos. O modelo de programação é baseado em uma representação de tempo discreto e composto da área de tancagem da refinaria, um terminal, e um poliduto. Além disto o duto é dividido em segmentos de volumes iguais como em Rejowski Jr e Pinto (2003). As principais variáveis de decisão são a direção da movimentação do duto (da refinaria para terminal ou do terminal para refinaria) e o que está sendo movimentado a cada intervalo. Estas decisões são formuladas através de uma representação disjuntiva. As disjunções são transformadas em uma formulação baseada em programação matemática mista-inteira, a partir da representação Convex-hull. A função objetivo considera os custos de estocagem, movimentação e interface de produtos. O modelo é aplicado inicialmente a um caso protótipo e posteriormente aplicado a um sistema real composto pelos terminais de São Sebastião e Guararema e o poliduto OSPLAN. Neste caso ao todo quatro famílias de produtos são transportadas: gasolina, querosene, nafta e diesel. A programação é gerada para o período de uma semana. / Pipeline systems play a major role in the supply chain of the petroleum industry. These systems are responsible for the transportation of most of the crude oil and petroleum derivatives. Pipeline systems transfer large amounts of different petroleum types and their products at a lower cost than any other transportation mode. Pipelines interconnect oil fields, ports, refineries, distribution centers (or depots), and consumer markets. The problem addressed is this work is based on a system that is composed by an oil refinery that must transfer multiple products through a single pipeline connected to one depot. The products are a set of petroleum derivatives that must be either transported from the refinery to the depot or from the depot to the refinery. Both depot and refinery also connect other refineries as well as other depots and customers, thus forming a complex transportation network. On the other hand, there are several demands that arise either from external customers or from refineries. The latter demand is due from the need of processing intermediate streams with components mixtures such as diluents, propane and diesel. In order to take advantage of the structure of the transportation network, it becomes beneficial and even necessary to operate the pipeline in both directions so that internal and external demands are satisfied. The objective of this work is to develop a mathematical model for the short term scheduling of a multiproduct pipeline system. The scheduling formulation must account for the bidirectionality of the multiproduct pipeline. In this context, the scheduling a multiproduct pipeline involves the from-to decision, the product amounts, their sequence and timing, in the optimal sense, considering all constrains on demands, production rates, inventories, and costs. The scheduling model is based on a discrete time representation and is composed by one refinery tank farm, one depot and one multiproduct pipeline. Moreover, the pipeline is divided into segments of equal volume, as in Rejowski Jr and Pinto (2003). The main decisions variables are the directions of transfer (refinery to depot or depot to refinery) and the types of products at each time interval. These decisions are formulated with a disjunctive representation. The disjunctions are represented in mixed integer formulation based on the convex-hull approach. The objective function involves inventory, transfer and product interface costs. The model is first applied to a prototype case and after applied to a real-world system that is composed of the São Sebastião and Guararema depot and the OSPLAN pipeline. Overall four families of products are transported: gasoline, kerosene, naphtha and oil diesel. These are scheduled over a period of one week.