890 resultados para utility maximization
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El propósito de la presente investigación es determinar si, a través del estudio y análisis de los estudios de tráfico en autopistas de peaje, se pueden determinar las razones de los incumplimientos en las previsiones de estos estudios. La metodología se basa en un análisis empírico ex- post facto de los estudios de tráfico contenidos en los anteproyectos de las autopistas Radial 3 y Radial 5 y los datos realmente verificados. Tras una introducción para presentar las principales características de las autopistas de peaje, se realiza una revisión de la bibliografía sobre el cumplimiento de las previsiones de tráfico. Lo anterior permite establecer una serie de aspectos que pueden contribuir a estos incumplimientos, así como una serie de medidas encontradas para mejorar las futuras previsiones. Ya en el núcleo fundamental de la investigación, esta se centra en el análisis del cumplimiento de las previsiones de tráfico contenidas en los anteproyectos de la Radial 3 y Radial 5. Se realiza un análisis crítico de la metodología adoptada, así como de las variables e hipótesis realizadas. Tras este primer análisis, se profundiza en la fase de asignación de los estudios. Siempre con base a los tráficos reales y para el año 2006, se cuantifica el efecto en los incumplimientos, por un lado de las variables utilizadas, y por otro, del propio método ó curva de asignación. Finalmente, y con base en los hallazgos anteriores, se determinan una serie de limitaciones en el método de asignación de tráficos entre recorridos alternativos para el caso de entornos urbanos usado. El planteamiento con base a las teorías del agente racional y maximización de la utilidad esperada es criticado desde la perspectiva de la teoría de decisión bajo condiciones de riesgo planteada por Kahneman y Tversky. Para superar las limitaciones anteriores, se propone una nueva curva de asignación semi empírica que relaciona la proporción del tráfico que circula por la autopista de peaje con la velocidad media en la autovía libre alternativa. ABSTRACT The aim of this research is to confirm whether the forensic analysis of the traffic forecast studies for tolled highways may bring to light the reasons behind the lack of accuracy. The methodology used on this research is empirical and is based on the ex –post facto analysis of the real traffic numbers compared to the forecasted for the tolled highways Radial 3 and Radial 5. Firstly the main features of tolled highways are presented as an introductory chapter. Secondly a broad bibliographic search is presented, this is done from a global perspective and from the Spanish perspective too. From this review, a list of the main causes behind the systematic inaccuracy together with measures to improve future traffic forecast exercises are shown. In what we could consider as the core of the research, it focuses on the ratios of actual / forecast traffic for the tolled highways Radial 3 y Radial 5 in Madrid outskirts. From a critical perspective, the methodology and inputs used in the traffic studies are analysed. In a further step, the trip assignment stage is scrutinised to quantify the influence of the inputs and the assignment model itself in the accuracy of the traffic studies. This exercise is bases on the year 2006. Finally, the assignment model used is criticised for its application in tolled urban highways. The assumptions behind the model, rational agent and expected utility maximization theories, are questioned under the theories presented by Kahneman and Tversky (Prospect Theory). To overcome these assignment model limitations, the author presents a semi empiric new diversion curve. This curve links the traffic proportion using the tolled highway and the average speed in the toll free alternative highway.
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Voters try to avoid wasting their votes even in PR systems. In this paper we make a case that this type of strategic voting can be observed and predicted even in PR systems. Contrary to the literature we do not see weak institutional incentive structures as indicative of a hopeless endeavor for studying strategic voting. The crucial question for strategic voting is how institutional incentives constrain an individual’s decision-making process. Based on expected utility maximization we put forward a micro-logic of an individual’s expectation formation process driven by institutional and dispositional incentives. All well-known institutional incentives to vote strategically that get channelled through the district magnitude are moderated by dispositional factors in order to become relevant for voting decisions. Employing data from Finland – because of its electoral system a particularly hard testing ground - we find considerable evidence for observable implications of our theory.
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This dissertation discussed resource allocation mechanisms in several network topologies including infrastructure wireless network, non-infrastructure wireless network and wire-cum-wireless network. Different networks may have different resource constrains. Based on actual technologies and implementation models, utility function, game theory and a modern control algorithm have been introduced to balance power, bandwidth and customers' satisfaction in the system. ^ In infrastructure wireless networks, utility function was used in the Third Generation (3G) cellular network and the network was trying to maximize the total utility. In this dissertation, revenue maximization was set as an objective. Compared with the previous work on utility maximization, it is more practical to implement revenue maximization by the cellular network operators. The pricing strategies were studied and the algorithms were given to find the optimal price combination of power and rate to maximize the profit without degrading the Quality of Service (QoS) performance. ^ In non-infrastructure wireless networks, power capacity is limited by the small size of the nodes. In such a network, nodes need to transmit traffic not only for themselves but also for their neighbors, so power management become the most important issue for the network overall performance. Our innovative routing algorithm based on utility function, sets up a flexible framework for different users with different concerns in the same network. This algorithm allows users to make trade offs between multiple resource parameters. Its flexibility makes it a suitable solution for the large scale non-infrastructure network. This dissertation also covers non-cooperation problems. Through combining game theory and utility function, equilibrium points could be found among rational users which can enhance the cooperation in the network. ^ Finally, a wire-cum-wireless network architecture was introduced. This network architecture can support multiple services over multiple networks with smart resource allocation methods. Although a SONET-to-WiMAX case was used for the analysis, the mathematic procedure and resource allocation scheme could be universal solutions for all infrastructure, non-infrastructure and combined networks. ^
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This dissertation is a discourse on the capital market and its interactive framework of acquisition and issuance of financial assets that drive the economy from both sides—investors/lenders and issuers/users of capital assets. My work consists of four essays in financial economics that offer a spectrum of revisions to this significant area of study. The first essay is a delineation of the capital market over the past half a century and major developments on capital markets on issues that pertain to the investor's opportunity set and the corporation's capital-raising availability set. This chapter should have merits on two counts: (i) a comprehensive account of capital markets and return-generating assets and (ii) a backdrop against which I present my findings in Chapters 2 through 4. ^ In Chapter 2, I rework on the Markowitz-Roy-Tobin structure of the efficient frontier and of the Separation Theorem. Starting off with a 2-asset portfolio and extending the paradigm to an n-asset portfolio, I bring out the optimal choice of assets for an investor under constrained utility maximization. In this chapter, I analyze the selection and revision-theoretic construct and bring out optimum choices. The effect of a change in perceived risk or return in the mind of an investor is ascertained on the portfolio composition. ^ Chapter 3 takes a look into corporations that issue market securities. The question of how a corporation decides what kinds of securities it should issue in the marketplace to raise funds brings out the classic value invariance proposition of Modigliani and Miller and fills the gap that existed in the literature for almost half a century. I question the general validity in the classic results of Modigliani and Miller and modify the existing literature on the celebrated value invariance proposition. ^ Chapter 4 takes the Modigliani-Miller regime to its correct prescription in the presence of corporate and personal taxes. I show that Modigliani-Miller's age-old proposition needs corrections and extensions, which I derive. ^ My dissertation overall brings all of these corrections and extensions to the existing literature as my findings, showing that capital markets are in an ever-changing state of necessary revision. ^
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The first chapter analizes conditional assistance programs. They generate conflicting relationships between international financial institutions (IFIs) and member countries. The experience of IFIs with conditionality in the 1990s led them to allow countries more latitude in the design of their reform programs. A reformist government does not need conditionality and it is useless if it does not want to reform. A government that faces opposition may use conditionality and the help of pro-reform lobbies as a lever to counteract anti-reform groups and succeed in implementing reforms.^ The second chapter analizes economies saddled with taxes and regulations. I consider an economy in which many taxes, subsidies, and other distortionary restrictions are in place simultaneously. If I start from an inefficient laissez-faire equilibrium because of some domestic distortion, a small trade tax or subsidy can yield a first-order welfare improvement, even if the instrument itself creates distortions of its own. This may result in "welfare paradoxes". The purpose of the chapter is to quantify the welfare effects of changes in tax rates in a small open economy. I conduct the simulation in the context of an intertemporal utility maximization framework. I apply numerical methods to the model developed by Karayalcin. I introduce changes in the tax rates and quantify both the impact on welfare, consumption and foreign assets, and the path to the new steady-state values.^ The third chapter studies the role of stock markets and adjustment costs in the international transmission of supply shocks. The analysis of the transmission of a positive supply shock that originates in one of the countries shows that on impact the shock leads to an inmediate stock market boom enjoying the technological advance, while the other country suffers from depress stock market prices as demand for its equity declines. A period of adjustment begins culminating in a steady state capital and output level that is identical to the one before the shock. The the capital stock of one country undergoes a non-monotonic adjustment. The model is tested with plausible values of the variables and the numeric results confirm the predictions of the theory.^
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The first chapter analizes conditional assistance programs. They generate conflicting relationships between international financial institutions (IFIs) and member countries. The experience of IFIs with conditionality in the 1990s led them to allow countries more latitude in the design of their reform programs. A reformist government does not need conditionality and it is useless if it does not want to reform. A government that faces opposition may use conditionality and the help of pro-reform lobbies as a lever to counteract anti-reform groups and succeed in implementing reforms. The second chapter analizes economies saddled with taxes and regulations. I consider an economy in which many taxes, subsidies, and other distortionary restrictions are in place simultaneously. If I start from an inefficient laissez-faire equilibrium because of some domestic distortion, a small trade tax or subsidy can yield a first-order welfare improvement, even if the instrument itself creates distortions of its own. This may result in "welfare paradoxes". The purpose of the chapter is to quantify the welfare effects of changes in tax rates in a small open economy. I conduct the simulation in the context of an intertemporal utility maximization framework. I apply numerical methods to the model developed by Karayalcin. I introduce changes in the tax rates and quantify both the impact on welfare, consumption and foreign assets, and the path to the new steady-state values. The third chapter studies the role of stock markets and adjustment costs in the international transmission of supply shocks. The analysis of the transmission of a positive supply shock that originates in one of the countries shows that on impact the shock leads to an inmediate stock market boom enjoying the technological advance, while the other country suffers from depress stock market prices as demand for its equity declines. A period of adjustment begins culminating in a steady state capital and output level that is identical to the one before the shock. The the capital stock of one country undergoes a non-monotonic adjustment. The model is tested with plausible values of the variables and the numeric results confirm the predictions of the theory.
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People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.
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People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.
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AMS subject classification: 90C05, 90A14.
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Kin selection theorists argue that evolution in social contexts will lead organisms to behave as if maximizing their inclusive, as opposed to personal, fitness. The inclusive fitness concept allows biologists to treat organisms as akin to rational agents seeking to maximize a utility function. Here we develop this idea and place it on a firm footing by employing a standard decision-theoretic methodology. We show how the principle of inclusive fitness maximization and a related principle of quasi-inclusive fitness maximization can be derived from axioms on an individual’s ‘as if preferences’ (binary choices). Our results help integrate evolutionary theory and rational choice theory, help draw out the behavioural implications of inclusive fitness maximization, and point to a possible way in which evolution could lead organisms to implement it.
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In the last decades there was an increase in stress at work and its effects on workers' health. These issues are still little studied in the electric utility sector. This study aims to evaluate factors associated with stress at work and to verify its associations with health status among workers of an electric company in São Paulo State, Brazil. A cross-sectional study was conducted with 474 subjects (87.5% of the eligible workers). Data were collected using self-reported questionnaires. A descriptive analysis, a multiple linear hierarchical regression analysis and a correlation analysis were performed. The majority of participants were males (91.1%) and the mean age was 37.5 yr. The mean score of stress level was 2.3 points (scale ranging from 1.0 to 5.0). Hierarchical multiple analyses showed that: regular practice of physical activities (p=0.025) and individual monthly income (p=0.002) were inversely associated with stress level; BMI was marginally associated with the stress level (p=0.074). The demographic characteristics were not associated with stress. Stress at work was significantly associated with physical and mental health status (p<0.001). To improve health of electric utility workers, actions are suggested to decrease stress by remuneration and an appropriate practice of physical activity aiming reduction of BMI
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In the last decades there was an increase in stress at work and its effects on workers' health. These issues are still little studied in the electric utility sector. This study aims to evaluate factors associated with stress at work and to verify its associations with health status among workers of an electric company in Sao Paulo State, Brazil. A cross-sectional study was conducted with 474 subjects (87.5% of the eligible workers). Data were collected using self-reported questionnaires. A descriptive analysis, a multiple linear hierarchical regression analysis and a correlation analysis were performed. The majority of participants were males (91.1%) and the mean age was 37.5 yr. The mean score of stress level was 2.3 points (scale ranging from 1.0 to 5.0). Hierarchical multiple analyses showed that: regular practice of physical activities (p=0.025) and individual monthly income (p=0.002) were inversely associated with stress level; BMI was marginally associated with the stress level (p=0.074). The demographic characteristics were not associated with stress. Stress at work was significantly associated with physical and mental health status (p<0.001). To improve health of electric utility workers, actions are suggested to decrease stress by remuneration and an appropriate practice of physical activity aiming reduction of BMI.
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Bittar CK, Cliquet A Jr, dos Santos Floter M: Utility of quantitative ultrasound of the calcaneus in diagnosing osteoporosis in spinal cord injury patients. Am J Phys Med Rehabil 2011;90:477-481. Objective: The aim of this study was to assess the utility of quantitative ultrasound of the calcaneus in diagnosing osteoporosis in spinal cord injury patients in a Brazilian Teaching Hospital. Design: This is a diagnostic test criterion standard comparison study. Between January 2008 and October 2009, the bone density of 15 spinal cord injury patients was assessed for analysis before beginning rehabilitation using muscle stimulation. The bone density was assessed using bone densitometry examination (DEXA) and ultrasound examination of the calcaneus (QUS). The measurements acquired using QUS and DEXA were compared between patients with spinal cord injury and a control group of ten healthy individuals. Results: The T-score values for femoral neck using DEXA (P < 0.0022) and those using QUS of the calcaneus (P < 0.0005) differed significantly between the groups, and the means in the normal subjects were higher than those in spinal cord injury patients who would receive electrical stimulation. In spinal cord injury patients, the significant differences were found between the QUS T-score for calcaneus and the DEXA scores for the lumbar spine and femoral neck. Conclusions: Because of the low level of mechanical stress on the calcaneus, the results of the QUS could not be correlated with the DEXA results for diagnosing osteoporosis. Therefore, QUS seems to be not a good choice for diagnosis and follow-up.
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Holden utility carrying members of the Federated Ship Painters and Dockers Union during the Labour Day march in 1965, Brisbane, Australia. Anti conscription banners can be seen in the background, and the facade of the Pearl Assurance Building.