1,372 research outputs found
Positive Mathematical Programming: a Comparison of Different Specification Rules
No full textIn this paper, the prescriptive capacity of different types of positive mathematical programming models applied to the Alentejo agricultural sector is analysed. Model results are compared for 2000 and 2004 agricultural price and subsidies scenarios, regarding optimal combination of activities. Thus, it is tested, on one hand, models capacity to reproduce Alentejo agricultural sector behaviour, and by the other hand, their response and adjustment capacities to changes in prices and in agricultural policy.Positive mathematical programming, agricultural supply, Alentejo, Research Methods/ Statistical Methods,
The proximal point algorithm without monotonicity
No full textWe study the proximal point algorithm in the setting in which the operator of inter-
est is metrically subregular and satisfies a submonoticity property. The latter can be viewed as
a quantified weakening of the standard definition of a monotone operator. Our main result gives
a condition under which, locally, the proximal point algorithm generates at least one sequence
which is linearly convergent to a zero of the underlying operator. General properties of our notion
of submonotonicity are also explored as well as connections to other concepts in the literature
The proximal point algorithm without monotonicity
No full textWe study the proximal point algorithm in the setting in which the operator of inter-
est is metrically subregular and satisfies a submonoticity property. The latter can be viewed as
a quantified weakening of the standard definition of a monotone operator. Our main result gives
a condition under which, locally, the proximal point algorithm generates at least one sequence
which is linearly convergent to a zero of the underlying operator. General properties of our notion
of submonotonicity are also explored as well as connections to other concepts in the literature
MATHEMATICAL PROGRAMMING FOR RESOURCE POLICY APPRAISAL UNDER MULTIPLE OBJECTIVES
No full textMathematical programming is one technique that can be used for resource policy appraisal. Multiple objectives are usually involved in resource policy considerations. This paper discusses issues regarding the use of mathematical programming techniques for the multiobjective resource policy arena. Theoretical models are introduced with a separation called for between producer response models and policy maker models due to a disparity of objectives. The paper draws on the literature citing cases where producer level models have been utilized to simulate the policy outcome implications of alternative policies.Resource /Energy Economics and Policy,
Mathematical Programming for Data Mining: Formulations and Challenges
No full textThis paper is intended to serve as an overview of a rapidly emerging research and applications area. In
addition to providing a general overview, motivating the importance of data mining problems within the
area of knowledge discovery in databases, our aim is to list some of the pressing research challenges, and
outline opportunities for contributions by the optimization research communities. Towards these goals, we
include formulations of the basic categories of data mining methods as optimization problems. We also
provide examples of successful mathematical programming approaches to some data mining problems
The Effect of Climate Change on Land Use and Wetlands Conservation in Western Canada: An Application of Positive Mathematical Programming
No full textThis study examines the impact of climate change on land use in the Prairie Pothole Region of Western Canada, with particular emphasis on how climate change will impact wetlands. A multi-region Positive Mathematical Programming model calibrates land use in the area to observed acreage in 2006. Policy simulations for both climate effects as well as the effects of biofuel policies determine how climate change will affect land use and wetlands. Given that the model calibrates to observed acreage, the policies provide a realistic view of how land use might change from current levels, given the effects of climate change. Results indicate that climate change could decrease wetlands in this area by as much as 50 percent. The effect will be very different depending on whether or not the social benefits of wetlands are considered, and the effects of climate change on wetlands are heterogeneous across the Prairie Provinces.Positive mathematical programming; wetlands conservation; land use change; climate change; biofuels; Prairie pothole region
A Fully Calibrated Generalized CES Programming Model of Agricultural Supply
No full textThe use of prior information on supply elasticities to calibrate programming models of agricultural supply has been advocated repeatedly in the recent literature (Heckelei and Britz 2005). Yet, Mérel and Bucaram (2009) have shown that the dual goal of calibrating such models to a reference allocation while replicating an exogenous set of supply elasticities is not always feasible. This article lays out the methodological foundation to exactly calibrate programming models of agricultural supply using generalized CES production functions. We formally derive the necessary and sufficient conditions under which such models can be calibrated to replicate the reference allocation while displaying crop-specific supply responses that are consistent with prior information. When it exists, the solution to the exact calibration problem is unique. From a microeconomic perspective, the generalized CES model is preferable to quadratic models that have been used extensively in policy analysis since the publication of Howitt’s (1995) Positive Mathematical Programming. The two types of specifications are also compared on the basis of their flexibility towards calibration, and it is shown that, provided myopic calibration is feasible, the generalized CES model can calibrate larger sets of supply elasticities than its quadratic counterpart. Our calibration criterion has relevance both for calibrated positive mathematical programming models and for “well-posed” models estimated through generalized maximum entropy following Heckelei and Wolff (2003), where it is deemed appropriate to include prior information regarding the value of own-price supply elasticities.Positive mathematical programming, generalized CES, supply elasticities, Crop Production/Industries, Production Economics,
A Methodological Note on the Estimation of Programming Models
No full textThe paper introduces a general methodological approach for the estimation of constrained optimisation models in agricultural supply analysis. It is based on optimality conditions of the desired programming model and shows a conceptual advantage compared to Positive Mathematical Programming in the context of well posed estimation problems. Moreover, it closes the empirical and methodological gap between programming models and duality based functional models with explicit allocation of fixed factors. Monte Carlo simulations are performed with a maximum entropy estimator to evaluate the functionality of the approach as well as the impact of empirically relevant prior information in small sample situations.Agricultural Supply Analysis, Programming Models, Maximum Entropy Estimation, Prior Information, Research Methods/ Statistical Methods,
A METHOD FOR INCLUDING IN PMP MODELS ACTIVITIES NON-EXISTENT IN THE BASELINE SITUATION
No full textWhen working with positive mathematical programming (PMP) models it is generally admitted that it is not possible to consider in the modeled unit activities that are not present in the baseline situation of the unit. This constitutes a considerable drawback for traditional PMP techniques which cannot be applied in specific cases, in particular to the study of the impact of new agri-environmental programs that subsidize crops grown with technologies different to those applied in the baseline situation. This paper presents a method for dealing with these cases, which can be easily implemented as an extension of the traditional calibration techniques of PMP. The method is applied to a specific problem, using modified calibration expressions derived from the necessary Khun-Tucker conditions, assuming increasing marginal costs. The analysis of the results and their comparison with those obtained using a linear programming model permits a first evaluation of this methodological proposal.Positive mathematical programming extensions, Agri-environmental measures, Environmental Economics and Policy,
NOVEL NUMERICAL PROCEDURES FOR LIMIT ANALYSIS OF STRUCTURES: MESH-FREE METHODS AND MATHEMATICAL PROGRAMMING
No full textCurrent research in the field of limit analysis is focussing on the development of
numerical tools which are sufficiently efficient and robust to be used in engineering
practice. This places demands on the numerical discretisation strategy adopted
as well as on the mathematical programming tools applied, which are the key
ingredients of a typical computational limit analysis procedure. In this research,
the Element-Free Galerkin (EFG) discretisation strategy is used to approximate
the displacement and moment fields in plate and slab problems, and second-order
cone programming (SOCP) is used to solve the resulting discretised formulations.
A numerical procedure using the EFG method and second-order cone programming
for the kinematic limit analysis problem was developed first. The moving
least squares technique was used in combination with a stabilised conforming nodal
integration scheme, both to keep the size of the optimisation problem small and to
provide stable and accurate solutions. The formulation was expressed as a problem
of minimizing a sum of Euclidean norms, which was then transformed into a
form suitable for solution using SOCP.
To improve the accuracy of solutions and to speed-up the computational process,
an efficient h-adaptive EFG scheme was also developed. The naturally conforming
property of meshfree approximations (with no nodal connectivity required) facilitates
the implementation of h-adaptivity. The error in the computed displacement
field was estimated accurately using the Taylor expansion technique. A stabilised
conforming nodal integration scheme was also extended to error estimators, leading
to an efficient and truly meshfree adaptive method.
To obtain an indication of bounds on the solutions obtained, an equilibrium formulation
was also developed. Pure moment fields were approximated using a
moving least squares technique. The collocation method was used to enforce the
strong form of the equilibrium equations and a stabilised conforming nodal integration
scheme was introduced to eliminate numerical instability problems. The von
Mises and Nielsen yield criteria were then enforced by introducing second-order
cone constraints
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