843 resultados para mathematical programming
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We study the role of natural resource windfalls in explaining the efficiency of public expenditures. Using a rich dataset of expenditures and public good provision for 1,836 municipalities in Peru for period 2001-2010, we estimate a non-monotonic relationship between the efficiency of public good provision and the level of natural resource transfers. Local governments that were extremely favored by the boom of mineral prices were more efficient in using fiscal windfalls whereas those benefited with modest transfers were more inefficient. These results can be explained by the increase in political competition associated with the boom. However, the fact that increases in efficiency were related to reductions in public good provision casts doubts about the beneficial effects of political competition in promoting efficiency.
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If the fundamental precepts of Farming Systems Research were to be taken literally then it would imply that for each farm 'unique' solutions should be sought. This is an unrealistic expectation, but it has led to the idea of a recommendation domain, implying creating a taxonomy of farms, in order to increase the general applicability of recommendations. Mathematical programming models are an established means of generating recommended solutions, but for such models to be effective they have to be constructed for 'truly' typical or representative situations. The multi-variate statistical techniques provide a means of creating the required typologies, particularly when an exhaustive database is available. This paper illustrates the application of this methodology in two different studies that shared the common purpose of identifying types of farming systems in their respective study areas. The issues related with the use of factor and cluster analyses for farm typification prior to building representative mathematical programming models for Chile and Pakistan are highlighted. (C) 2003 Elsevier Science Ltd. All rights reserved.
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The games-against-nature approach to the analysis of uncertainty in decision-making relies on the assumption that the behaviour of a decision-maker can be explained by concepts such as maximin, minimax regret, or a similarly defined criterion. In reality, however, these criteria represent a spectrum and, the actual behaviour of a decision-maker is most likely to embody a mixture of such idealisations. This paper proposes that in game-theoretic approach to decision-making under uncertainty, a more realistic representation of a decision-maker's behaviour can be achieved by synthesising games-against-nature with goal programming into a single framework. The proposed formulation is illustrated by using a well-known example from the literature on mathematical programming models for agricultural-decision-making. (c) 2005 Elsevier Inc. All rights reserved.
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The member countries of the World Health Organization have endorsed its Global Strategy on Diet, Physical Activity, and Health. We assess the potential consumption impacts of these norms in the United States, France, and the United Kingdom using a mathematical programming approach. We find that adherence would involve large reductions in the consumption of fats and oils accompanying large rises in the consumption of fruits, vegetables, and cereal. Further, in the United Kingdom and the United States, but not France, sugar intakes would have to shrink considerably. Focusing on sub-populations within each country, we find that the least educated, not necessarily the poorest, would have to bear the highest burden of adjustment.
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Promotion of adherence to healthy-eating norms has become an important element of nutrition policy in the United States and other developed countries. We assess the potential consumption impacts of adherence to a set of recommended dietary norms in the United States using a mathematical programming approach. We find that adherence to recommended dietary norms would involve significant changes in diets, with large reductions in the consumption of fats and oils along with large increases in the consumption of fruits, vegetables, and cereals. Compliance with norms recommended by the World Health Organization for energy derived from sugar would involve sharp reductions in sugar intakes. We also analyze how dietary adjustments required vary across demographic groups. Most socio-demographic characteristics appear to have relatively little influence on the pattern of adjustment required to comply with norms, Income levels have little effect on required dietary adjustments. Education is the only characteristic to have a significant influence on the magnitude of adjustments required. The least educated rather than the poorest have to bear the highest burden of adjustment. Out- analysis suggests that fiscal measures like nutrient-based taxes may not be as regressive as commonly believed. Dissemination of healthy-eating norms to the less educated will be a key challenge for nutrition policy.
Resumo:
Promotion of adherence to healthy-eating norms has become an important element of nutrition policy in the United States and other developed countries. We assess the potential consumption impacts of adherence to a set of recommended dietary norms in the United States using a mathematical programming approach. We find that adherence to recommended dietary norms would involve significant changes in diets, with large reductions in the consumption of fats and oils along with large increases in the consumption of fruits, vegetables, and cereals. Compliance with norms recommended by the World Health Organization for energy derived from sugar would involve sharp reductions in sugar intakes. We also analyze how dietary adjustments required vary across demographic groups. Most socio-demographic characteristics appear to have relatively little influence on the pattern of adjustment required to comply with norms, Income levels have little effect on required dietary adjustments. Education is the only characteristic to have a significant influence on the magnitude of adjustments required. The least educated rather than the poorest have to bear the highest burden of adjustment. Out- analysis suggests that fiscal measures like nutrient-based taxes may not be as regressive as commonly believed. Dissemination of healthy-eating norms to the less educated will be a key challenge for nutrition policy.
Resumo:
The member countries of the World Health Organization (WHO) have recently endorsed its global strategy on diet, physical activity and health. The strategy emphasises the need to limit the consumption of saturated fats and trans-fatty acids, salt and sugars, and to increase consumption of fruits and vegetables in order to combat the growing burden of non-communicable diseases. This paper attempts a broad quantitative assessment of the consumption impacts of these norms in OECD countries using a mathematical programming approach. We find that adherence to the WHO norms would involve a significant decrease in the consumption of vegetable oils (30%), dairy products (28%), sugar (24%), animal fats (30%) and meat (pig meat, 13.5%, mutton and goat 14.5%) and a significant increase in the human consumption of cereals (31%), fruits (25%) and vegetables (21%). (c) 2005 Elsevier Ltd. All rights reserved.
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A novel global optimization method based on an Augmented Lagrangian framework is introduced for continuous constrained nonlinear optimization problems. At each outer iteration k the method requires the epsilon(k)-global minimization of the Augmented Lagrangian with simple constraints, where epsilon(k) -> epsilon. Global convergence to an epsilon-global minimizer of the original problem is proved. The subproblems are solved using the alpha BB method. Numerical experiments are presented.
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In the late seventies, Megiddo proposed a way to use an algorithm for the problem of minimizing a linear function a(0) + a(1)x(1) + ... + a(n)x(n) subject to certain constraints to solve the problem of minimizing a rational function of the form (a(0) + a(1)x(1) + ... + a(n)x(n))/(b(0) + b(1)x(1) + ... + b(n)x(n)) subject to the same set of constraints, assuming that the denominator is always positive. Using a rather strong assumption, Hashizume et al. extended Megiddo`s result to include approximation algorithms. Their assumption essentially asks for the existence of good approximation algorithms for optimization problems with possibly negative coefficients in the (linear) objective function, which is rather unusual for most combinatorial problems. In this paper, we present an alternative extension of Megiddo`s result for approximations that avoids this issue and applies to a large class of optimization problems. Specifically, we show that, if there is an alpha-approximation for the problem of minimizing a nonnegative linear function subject to constraints satisfying a certain increasing property then there is an alpha-approximation (1 1/alpha-approximation) for the problem of minimizing (maximizing) a nonnegative rational function subject to the same constraints. Our framework applies to covering problems and network design problems, among others.
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In this note we discuss the convergence of Newton`s method for minimization. We present examples in which the Newton iterates satisfy the Wolfe conditions and the Hessian is positive definite at each step and yet the iterates converge to a non-stationary point. These examples answer a question posed by Fletcher in his 1987 book Practical methods of optimization.
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Two Augmented Lagrangian algorithms for solving KKT systems are introduced. The algorithms differ in the way in which penalty parameters are updated. Possibly infeasible accumulation points are characterized. It is proved that feasible limit points that satisfy the Constant Positive Linear Dependence constraint qualification are KKT solutions. Boundedness of the penalty parameters is proved under suitable assumptions. Numerical experiments are presented.
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The objective in the facility location problem with limited distances is to minimize the sum of distance functions from the facility to the customers, but with a limit on each distance, after which the corresponding function becomes constant. The problem has applications in situations where the service provided by the facility is insensitive after a given threshold distance (eg. fire station location). In this work, we propose a global optimization algorithm for the case in which there are lower and upper limits on the numbers of customers that can be served
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This work aims to "build" rostering urban bus crews to minimize the cost of overtime. For this purpose a mathematical model was developed based on case study in an urban transport company in the metropolitan region of Natal. This problem is usually known in the literature as the Crew Scheduling Problem (CSP) and classified as NP-hard. The mathematical programming takes into account constraints such as: completion of all trips, daily and maximum allowable range of home and / or food. We used the Xpress-MP software to implement and validate the proposed model. For the tested instances the application of the model allowed a reduction in overtime from 38% to 84%
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)