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Статті в журналах з теми "Production function (dual and primal)"
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Paris, Quirino. "Certezze e novitŕ in economia della produzione." QA Rivista dell'Associazione Rossi-Doria, no. 3 (August 2009): 7–22. http://dx.doi.org/10.3280/qu2009-003001.
Повний текст джерелаАнотація:
- Michele De Benedictis has for some time taken an interest in behavioral models for agricultural entrepreneurs. Often, such models are specified by means of a production function and a cost function with the associated derived demands for inputs. In order to make such models operational in a given empirical setting, the approach in the traditional literature has been to estimate either the production function and the associated first order conditions or the system of derived demand functions for inputs. This paper proposes an encompassing approach which consists in the joint estimation of the production function and the associated first order conditions and the system of derived demand functions. Empirical verification lends support to the hypothesis that full utilization of the available information requires a primal-dual approach, as presented in this paper.EconLit Classification: C600, D210Keywords: Production Function, Cost Function, Primal-Dual Method, Joint EstimationParole chiave: Funzione di produzione, Funzione di costo, Metodo primario-duale, Stima congiunta
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Sugianto, Welly. "OPTIMASI KAPASITAS PRODUKSI UKM DENGAN GOAL PROGRAMMING." JURNAL REKAYASA SISTEM INDUSTRI 5, no. 2 (May 30, 2020): 146. http://dx.doi.org/10.33884/jrsi.v5i2.1911.
Повний текст джерелаАнотація:
UKM Jovelyn is a small medium enterprise (SME) that engaged in the field of bakery production. Until now, they produce cakes and cookies. They sell products throughout the Batam area which includes (Tiban market, aviari market, mitra market and puja bahari market), shops, school canteens and so on. The SME targets several things such as profit per month, number of hours worked, number of overtime hours, machine utilities, labor utilities and so forth. Until now, the SME has not been able to reach the targets because the UKM has not determined the production amount based on the appropriate calculation. The number of products made is determined only on an intuitive basis. Determination of the amount of production cannot be determined by the usual simplex method because the objective function in the usual simplex method contains a target. Problem solving is done by using goal programming. The results of the calculation analysis show that to achieve the optimal value, the SME must produce coconut root cookies, butter cookies, nastar cookies, snow princess cookies and peanut cookies respectively 11.89 kg, 22.43 kg, 24.96 kg , 1.97kg and 0 kg. Sensitivity analysis is carried out after there are changes in conditions that result in changes in the linear program matrix, so the number of products that must be made also changes which include coconut root cookies as much as 12.8 kg, as much as 16.91 kg of butter cookies, nastar cookies as much as 25.7 and the last is 3.39 kg of nut cookies which in the initial calculation, nut cookies were not produced. The sensitivity analysis is not done by recalculation but rather by modifying the matrix and completing iteration with primal dual.
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Xing, Yumei, and Dong Qiu. "Solving Triangular Intuitionistic Fuzzy Matrix Game by Applying the Accuracy Function Method." Symmetry 11, no. 10 (October 9, 2019): 1258. http://dx.doi.org/10.3390/sym11101258.
Повний текст джерелаАнотація:
In this paper, the matrix game based on triangular intuitionistic fuzzy payoff is put forward. Then, we get a conclusion that the equilibrium solution of this game model is equivalent to the solution of a pair of the primal–dual single objective intuitionistic fuzzy linear optimization problems ( I F L O P 1 ) and ( I F L O D 1 ) . Furthermore, by applying the accuracy function, which is linear, we transform the primal–dual single objective intuitionistic fuzzy linear optimization problems ( I F L O P 1 ) and ( I F L O D 1 ) into the primal–dual discrete linear optimization problems ( G L O P 1 ) and ( G L O D 1 ) . The above primal–dual pair ( G L O P 1 ) – ( G L O D 1 ) is symmetric in the sense the dual of ( G L O D 1 ) is ( G L O P 1 ) . Thus the primal–dual discrete linear optimization problems ( G L O P 1 ) and ( G L O D 1 ) are called the symmetric primal–dual discrete linear optimization problems. Finally, the technique is illustrated by an example.
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Sheu, Ruey-Lin, and Shu-Cherng Fang. "On the relationship of interior-point methods." International Journal of Mathematics and Mathematical Sciences 16, no. 3 (1993): 565–72. http://dx.doi.org/10.1155/s0161171293000699.
Повний текст джерелаАнотація:
In this paper, we show that the moving directions of the primal-affine scaling method (with logarithmic barrier function), the dual-affine scaling method (with logarithmic barrier function), and the primal-dual interior point method are merely the Newton directions along three different algebraic paths that lead to a solution of the Karush-Kuhn-Tucker conditions of a given linear programming problem. We also derive the missing dual information in the primal-affine scaling method and the missing primal information in the dual-affine scaling method. Basically, the missing information has the same form as the solutions generated by the primal-dual method but with different scaling matrices.
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Mundlak, Yair. "Production Function Estimation: Reviving the Primal." Econometrica 64, no. 2 (March 1996): 431. http://dx.doi.org/10.2307/2171790.
Повний текст джерела
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Tanikawa, A., and H. Mukai. "New Lagrangian function for nonconvex primal-dual decomposition." Computers & Mathematics with Applications 13, no. 8 (1987): 661–76. http://dx.doi.org/10.1016/0898-1221(87)90039-3.
Повний текст джерела
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Huang, Zhiyi, and Anthony Kim. "Welfare maximization with production costs: A primal dual approach." Games and Economic Behavior 118 (November 2019): 648–67. http://dx.doi.org/10.1016/j.geb.2018.03.003.
Повний текст джерела
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Kumbhakar, Subal C., and Efthymios G. Tsionas. "Stochastic error specification in primal and dual production systems." Journal of Applied Econometrics 26, no. 2 (June 16, 2009): 270–97. http://dx.doi.org/10.1002/jae.1100.
Повний текст джерела
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Xing, Wenxun, Shu-Cherng Fang, Ruey-Lin Sheu, and Liping Zhang. "Canonical Dual Solutions to Quadratic Optimization over One Quadratic Constraint." Asia-Pacific Journal of Operational Research 32, no. 01 (February 2015): 1540007. http://dx.doi.org/10.1142/s0217595915400072.
Повний текст джерелаАнотація:
A quadratic optimization problem with one nonconvex quadratic constraint is studied using the canonical dual approach. Under the dual Slater's condition, we show that the canonical dual has a smooth concave objective function over a convex feasible domain, and this dual has a finite supremum unless the original quadratic optimization problem is infeasible. This supremum, when it exists, always equals to the minimum value of the primal problem. Moreover, a global minimizer of the primal problem can be provided by a dual-to-primal conversion plus a "boundarification" technique. Application to solving a quadratic programming problem over a ball is included and an error bound estimation is provided.
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Ye, Xugang, Shih-Ping Han, and Anhua Lin. "A Note on the Connection Between the Primal-Dual and the A* Algorithm." International Journal of Operations Research and Information Systems 1, no. 1 (January 2010): 73–85. http://dx.doi.org/10.4018/joris.2010101305.
Повний текст джерелаАнотація:
The primal-dual algorithm for linear programming is very effective for solving network flow problems. For the method to work, an initial feasible solution to the dual is required. In this article, we show that, for the shortest path problem in a positively weighted graph equipped with a consistent heuristic function, the primal-dual algorithm will become the well-known A* algorithm if a special initial feasible solution to the dual is chosen. We also show how the improvements of the dual objective are related to the A* iterations.
Дисертації з теми "Production function (dual and primal)"
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Devilliers, Esther. "Modélisation micro-économétrique des choix de pratiques de production et des utilisations d'intrants chimiques des agriculteurs : une approche par les fonctions de production latentes." Thesis, Rennes, Agrocampus Ouest, 2021. http://www.theses.fr/2021NSARE058.
Повний текст джерелаАнотація:
La notion d’itinéraire technique est une notion agronomique qui nous permet d’appréhender l’imbrication entre les rendements objectifs et les niveaux d’utilisation d’intrants associés. Dès lors, on peut admettre qu’à différents types d’itinéraires techniques correspondent différentes fonctions de production. Modéliser ces différentes fonctions est une des clés pour mieux comprendre la dépendance de certaines pratiques culturales aux pesticides et de ce fait constitue un enjeu majeur pour concevoir les futures politiques publiques.Intégrer cette notion d’itinéraire technique nécessite de tenir compte de l’interdépendance entre les choix de ces pratiques, leur rendement et les utilisations associées. Pour ce faire, on considère des modèles de changement de régime endogène qui permettent de contrôler des biais de sélection. Lorsque ces pratiques sont inobservées, on définit la séquence de choix comme processus Markovien.Le modèle résultant nous permet de recouvrir les pratiques culturales, leurs niveaux de rendement et d’utilisation d’intrants ainsi que la dynamique de choix des dites pratiques. Lorsque ces pratiques sont observées, on décide de considérer un modèle primal afin de pouvoir vérifier le rôle différencié des pesticides et évaluer l’effet des politiques publiques conjointement sur les rendements et les niveaux d’utilisation d’intrants chimiques.En bref, cette thèse vise à donner des outils pour évaluer au mieux les effets des politiques agro-environnementales sur les utilisations de pesticides, les rendements et mes choix de pratiques culturales des agriculteursCropping management practices is an agronomic notion grasping the interdependence between targeted yield and input use levels. Subsequently, one can legitimately assume that different cropping management practices are associated to different production functions. To better understand pesticide dependence – a key point to encourage more sustainable practices – one have to consider modelling cropping management practices specific production functions.Because of the inherent interdependence between those practices and their associeted yield and input use levels, we need to consider endogenous regime switching models.When unobserved, the sequence of cropping management practices choices is considered as a Markovian process. From this modelling framework we can derive the cropping management choices, their dynamics, their associated yield and input use levels. When observed, we consider primal production functions to see how yield responds differently to input uses based on the different cropping management practices. Thus, we can assess jointly the effect of a public policy on input use and yield levels.In a nutshell, in this PhD we are aiming at giving some tools to evaluate the differentiated effect of agri-environmental public policies on production choies and on the associated yield and input use levels
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Madabushi, Ananth R. "Lagrangian Relaxation / Dual Approaches For Solving Large-Scale Linear Programming Problems." Thesis, Virginia Tech, 1997. http://hdl.handle.net/10919/36833.
Повний текст джерелаАнотація:
This research effort focuses on large-scale linear programming problems that arise in the context of solving various problems such as discrete linear or polynomial, and continuous nonlinear, nonconvex programming problems, using linearization and branch-and-cut algorithms for the discrete case, and using polyhedral outer-approximation methods for the continuous case. These problems arise in various applications in production planning, location-allocation, game theory, economics, and many engineering and systems design problems. During the solution process of discrete or continuous nonconvex problems using polyhedral approaches, one has to contend with repeatedly solving large-scale linear programming(LP) relaxations. Thus, it becomes imperative to employ an efficient method in solving these problems. It has been amply demonstrated that solving LP relaxations using a simplex-based algorithm, or even an interior-point type of procedure, can be inadequately slow ( especially in the presence of complicating constraints, dense coefficient matrices, and ill-conditioning ) in comparison with a Lagrangian Relaxation approach. With this motivation, we present a practical primal-dual subgradient algorithm that incorporates a dual ascent, a primal recovery, and a penalty function approach to recover a near optimal and feasible pair of primal and dual solutions.
The proposed primal-dual approach is comprised of three stages. Stage I deals with solving the Lagrangian dual problem by using various subgradient deflection strategies such as the Modified Gradient Technique (MGT), the Average Direction Strategy (ADS), and a new direction strategy called the Modified Average Direction Strategy (M-ADS). In the latter, the deflection parameter is determined based on the process of projecting the unknown optimal direction onto the space spanned by the current subgradient direction and the previous direction. This projected direction approximates the desired optimal direction as closely as possible using the conjugate subgradient concept. The step-length rules implemented in this regard are the Quadratic Fit Line Search Method and a new line search method called the Directional Derivative Line Search Method in which we start with a prescribed step-length and then ascertain whether to increase or decrease the step-length value based on the right-hand and left-hand derivative information available at each iteration. In the second stage of the algorithm (Stage II), a sequence of updated primal solutions is generated using some convex combinations of the Lagrangian subproblem solutions. Alternatively, a starting primal optimal solution can be obtained using the complementary slackness conditions. Depending on the extent of feasibility and optimality attained, Stage III applies a penalty function method to improve the obtained primal solution toward a near feasible and optimal solution.
We present computational experience using a set of randomly generated, structured, linear programming problems of the type that might typically arise in the context of discrete optimization.Master of Science
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Stanzani, Amélia de Lorena [UNESP]. "Método previsor-corretor primal-dual de pontos interiores em problemas multiobjetivo de despacho econômico e ambiental." Universidade Estadual Paulista (UNESP), 2012. http://hdl.handle.net/11449/87196.
Повний текст джерелаАнотація:
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O presente trabalho apresenta o método primal-dual previsor-corretor de pontos interiores para programação quadrática, com restrições lineares e quadráticos e variáveis canalizadas, e a aplicação deste método na resolução de problemas multiobjetivo de despacho econômico e ambiental, encontrados na engenharia elétrica. Pretende-se determinar soluções que sejam eficientes em relação ao custo dos combustíveis empregados na geração termoelétrica de energia e ao controle da emissão de poluentes, investigando-se duas estratégias: a primeira estratégica considera na função objetivo a soma ponderada entre as funções objetivo econômica e objetivo ambiental; a segunda estratégia considera o problema de despacho econômico condicionado à restrição ambiental, limitada superiormente para níveis permissíveis de missão. Para a resolução destes, uma implementação computacional do método primal-dual foi realizada em linguagem de programação C++, considerando o procedimento previsor-corretor com uma estratégia de barreira modificada para as restrições quadráticas de desigualdade, quando consideramos a segunda estratégia. Os resultados obtidos demonstram a eficiência do método em destaque em comparação a outros métodos como algoritmos genéticos co-evolutivo, atávico híbrido e cultural, bem como ao método primal-dual de pontos interiores, com procedimento de busca unidimensional, que estão divulgados na literatura
This paper presents the primal-dual predictor-corrector interior point method for quadratic programming with linear and quadratic constraints and bounded variables, and its application in multiobjective problems of economic and environmental dispatch, found in electrical engineering. It is intended to determine effective solutions to the fuel cost used in thermal power generation and emissions control, by investigating two strategy; the first strategy considers the objective function as weighted sum of economic and environmental objective functions; the second strategy considers the economic dispatch problem subject to environmental constraint, upper bounded for allowable emission levels. To solve them, a computational implementation of primal-dual methods was performed in C++ programming language, considering the predictor-corrector procedure with a strategy of modified barrier for the quadratic inequality constraints, when we considerer the second strategy. The results obtained demonstrate the efficiency of the method highlighted in comparison with the co-evolutive genetic algorithms, hybrid and atavistic cultural, as well the primal-dual interior point method with one-dimensional search procedure, which are found in the literature
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Stanzani, Amélia de Lorena. "Método previsor-corretor primal-dual de pontos interiores em problemas multiobjetivo de despacho econômico e ambiental /." Bauru : [s.n.], 2012. http://hdl.handle.net/11449/87196.
Повний текст джерелаАнотація:
Orientador: Antonio Roberto BalboBanca: Helenice de Oliveira F. Silva
Banca: Edmea Cassia Baptista
Resumo: O presente trabalho apresenta o método primal-dual previsor-corretor de pontos interiores para programação quadrática, com restrições lineares e quadráticos e variáveis canalizadas, e a aplicação deste método na resolução de problemas multiobjetivo de despacho econômico e ambiental, encontrados na engenharia elétrica. Pretende-se determinar soluções que sejam eficientes em relação ao custo dos combustíveis empregados na geração termoelétrica de energia e ao controle da emissão de poluentes, investigando-se duas estratégias: a primeira estratégica considera na função objetivo a soma ponderada entre as funções objetivo econômica e objetivo ambiental; a segunda estratégia considera o problema de despacho econômico condicionado à restrição ambiental, limitada superiormente para níveis permissíveis de missão. Para a resolução destes, uma implementação computacional do método primal-dual foi realizada em linguagem de programação C++, considerando o procedimento previsor-corretor com uma estratégia de barreira modificada para as restrições quadráticas de desigualdade, quando consideramos a segunda estratégia. Os resultados obtidos demonstram a eficiência do método em destaque em comparação a outros métodos como algoritmos genéticos co-evolutivo, atávico híbrido e cultural, bem como ao método primal-dual de pontos interiores, com procedimento de busca unidimensional, que estão divulgados na literatura
Abstract: This paper presents the primal-dual predictor-corrector interior point method for quadratic programming with linear and quadratic constraints and bounded variables, and its application in multiobjective problems of economic and environmental dispatch, found in electrical engineering. It is intended to determine effective solutions to the fuel cost used in thermal power generation and emissions control, by investigating two strategy; the first strategy considers the objective function as weighted sum of economic and environmental objective functions; the second strategy considers the economic dispatch problem subject to environmental constraint, upper bounded for allowable emission levels. To solve them, a computational implementation of primal-dual methods was performed in C++ programming language, considering the predictor-corrector procedure with a strategy of modified barrier for the quadratic inequality constraints, when we considerer the second strategy. The results obtained demonstrate the efficiency of the method highlighted in comparison with the co-evolutive genetic algorithms, hybrid and atavistic cultural, as well the primal-dual interior point method with one-dimensional search procedure, which are found in the literature
Mestre
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Mazal, Camila Mara Nardello. "Funções penalidade para variáveis discretas e o problema de fluxo de potência ótimo reativo /." Bauru, 2019. http://hdl.handle.net/11449/191282.
Повний текст джерелаАнотація:
Orientador: Edméa Cássia BaptistaResumo: O problema de fluxo de potência ótimo reativo é representado matematicamente por um problema de otimização não linear, restrito, não convexo, de grande porte e com variáveis de controle contínuas e discretas. A representação dos taps dos transformadores em fase e das susceptâncias shunt dos bancos de capacitores/reatores do sistema como variáveis discretas, torna o problema mais próximo da realidade. Entretanto, problemas de otimização não linear com variáveis discretas apresentam dificuldades em sua resolução, as quais são impostas pelas variáveis discretas. Uma das técnicas para sua resolução consiste em utilizar funções penalidades para tratar as variáveis discretas. Desta forma, transforma-se o problema discreto em uma sequência de problemas contínuos, e o método primal-dual barreira logarítmica pode ser utilizado para resolver esses problemas. Neste trabalho o objetivo é analisar a convergência do método de penalidade para variáveis discretas aplicado ao problema de fluxo de potência ótimo reativo, ao se utilizar diferentes funções penalidade e a combinação delas. Testes computacionais foram realizados com um exemplo númérico e com os sistemas elétricos IEEE 14, 30 e 118 barras, utilizando o pacote de otimização KNITRO em interface com o software GAMS. Os resultados demonstram que a combinação de diferentes funções penalidade para o tratamento das variáveis discretas é promissora.
Abstract: The reactive optimal power flow problem is mathematically represented by a nonlinear, constrained, nonconvex, large scale optimization problem with continuous and discrete control variables. The representation of the in-phase transformers taps and/or the shunt susceptances of capacitor/reactor Banks of the system, as discrete variables, make the problem closer to reality. Nonlinear optimization problems with discrete variables are difficulty to solve, due to the discrete variables. One of the soluction techniques consist in using penalty functions to treat the discrete variables. Thus, the discrete problem is transformed in a sequence of continuous problems, and the primal dual logarithmic barrier method can be used to solve these problems. In this work the objective is to analyze the convergence of the penalty method for discrete variables applied to the reactive optimal power flow problem, by using different penalty functions and the mixture of them. Computational tests have been carried out with a numerical example and with the IEEE 14, 30 and 118 buses electrical systems, using the KNITRO optimization package in interface with the GAMS software. The results show that a mixture of different penalty functions for treatment of discrete variable is advantageous.
Mestre
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Costa, Marina Teixeira [UNESP]. "Solução do problema de fluxo de potência ótimo com restrição de segurança e controles discretos utilizando o método primal-dual barreira logarítmica." Universidade Estadual Paulista (UNESP), 2016. http://hdl.handle.net/11449/148774.
Повний текст джерелаАнотація:
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
O problema de Fluxo de Potência Ótimo determina a melhor condição de operação de um sistema elétrico de potência. Há diferentes classes de problemas de Fluxo de Potência Ótimo de acordo com os tipos de funções a serem otimizadas, e os conjuntos de controles e de restrições utilizados. Dentre elas, dá-se destaque ao problema de Fluxo de Potência Ótimo com Restrição de Segurança, o qual é uma importante ferramenta para os Operadores dos Sistemas de Transmissão, tanto para o planejamento operacional, quanto para a precificação da energia. Seu objetivo é minimizar os custos operacionais de geração de energia levando em consideração as restrições decorrentes da operação do sistema sob um conjunto de contingências. Ele é formulado como um problema de otimização não linear, não-convexo de grande porte, com variáveis contínuas e discretas. Neste trabalho investiga-se este problema em relação à sua formulação, dificuldades computacionais e método de solução. Para um tratamento do problema mais próximo à realidade adotam-se alguns controles como variáveis discretas, ou seja, os taps dos transformadores. Estes são tratados através de um método que penaliza a função objetivo quando as variáveis discretas assumem valores não discretos. Desta forma, o problema não linear discreto é transformado em um problema contínuo e o método Primal-Dual Barreira Logarítmica é utilizado em sua resolução. Testes computacionais são apresentados com o problema de Fluxo de Potência Ótimo com Restrição de Segurança associado ao sistema teste IEEE 14 barras em três etapas de teste. Os resultados obtidos e as comparações realizadas comprovam a eficiência do método de resolução escolhido
The Optimum Power Flow problem determines the best operating condition of an electric power system. There are different classes of Optimal Power Flow problems according to the types of functions to be optimized, and the sets of controls and constraints used. Among them, the problem of Optimal Power Flow with Security Constraint is highlighted, which is an important tool for the Transmission System operators, both for operational planning and for energy pricing. Its objective is to minimize the operational costs of power generation taking into account the constraints arising from the operation of the system under a set of contingencies. It is formulated as a nonlinear, nonconvex large optimization problem, of continuous and discrete variables. In this work, the problem in relation to its formulation, computational difficulties and solution method is investigated. For a treatment of the problem closest to the reality, some controls such as discrete variables, i.e. the taps of the transformers, are used. These are treated by a method that penalizes the objective function when the discrete variables assume non-discrete values. Thus, the discrete nonlinear problem is transformed into a continuous problem and the Primal-Dual Logarithmic Barrier method is used in its resolution. Computational tests are performed with the optimal power flow problem with security constraint associated with the test system of IEEE 14 bars in three test stages. The obtained results and the realized comparisons prove the efficiency of the chosen resolution method.
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Trienis, Michael Joseph. "Computational convex analysis : from continuous deformation to finite convex integration." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/2799.
Повний текст джерелаАнотація:
After introducing concepts from convex analysis, we study how to continuously transform one convex
function into another. A natural choice is the arithmetic average, as it is pointwise continuous;
however, this choice fails to average functions with different domains. On the contrary, the proximal
average is not only continuous (in the epi-topology) but can actually average functions with
disjoint domains. In fact, the proximal average not only inherits strict convexity (like the arithmetic
average) but also inherits smoothness and differentiability (unlike the arithmetic average).
Then we introduce a computational framework for computer-aided convex analysis. Motivated
by the proximal average, we notice that the class of piecewise linear-quadratic (PLQ) functions is
closed under (positive) scalar multiplication, addition, Fenchel conjugation, and Moreau envelope.
As a result, the PLQ framework gives rise to linear-time and linear-space algorithms for convex
PLQ functions. We extend this framework to nonconvex PLQ functions and present an explicit
convex hull algorithm.
Finally, we discuss a method to find primal-dual symmetric antiderivatives from cyclically monotone
operators. As these antiderivatives depend on the minimal and maximal Rockafellar functions
[5, Theorem 3.5, Corollary 3.10], it turns out that the minimal and maximal function in [12,
p.132,p.136] are indeed the same functions. Algorithms used to compute these antiderivatives can
be formulated as shortest path problems.
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Souza, Rafael Ramos de [UNESP]. "Um método primal-dual de pontos interiores/exteriores com estratégias de teste quadrático e determinação de direções de busca combinadas no problema de fluxo de potência ótimo reativo." Universidade Estadual Paulista (UNESP), 2016. http://hdl.handle.net/11449/142853.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
O problema de Fluxo de Potência Ótimo tem por objetivo a otimização de um critério de desempenho elétrico sujeito ao atendimento das demandas de potência ativa e reativa em cada barra e de restrições técnico-operacionais dos sistemas de geração e transmissão. É um problema de otimização, não-linear, não-convexo e de grande porte. Neste trabalho é explorado o problema de Fluxo de Potência Ótimo Reativo com o objetivo de minimizar as perdas de potência ativa na transmissão e para resolvê-lo é proposto um método primal-dual de pontos interiores/exteriores barreira logarítmica modificada com estratégias de teste quadrático e determinação de direções de busca combinadas. O teste quadrático é proposto como alternativa ao procedimento de Cholesky na verificação da positividade da matriz hessiana do problema, que, se definida positiva, garante direções de descida para o método. As novas direções de busca são determinadas através de combinações das direções dos procedimentos previsor e corretor, determinadas através da análise das condições de complementaridade das variáveis primais e duais do problema. O método proposto foi implementado em Matlab e aplicado aos sistemas elétricos 9 e 39 barras e aos sistemas IEEE 14, 30, 57 e 118 barras. O desempenho do método com as estratégias propostas é avaliado em termos do número de iterações e do tempo computacional. Os resultados são promissores e permitem a aplicação do presente método, com as estratégias propostas, para resolver o problema de Fluxo de Potência Ótimo Reativo com maior dimensão do que os sistemas testados.
The reactive optimal power flow problem is concerned with the optimization of a specific criterion associated with the transmission system while enforcing the power balance in each transmission bus, as well as operational and physical constraints associated with generation and transmission systems. It is a nonlinear, non-convex and large optimization problem. In this work we consider the active losses minimization in the transmission system as a criterion for the optimal power flow problem. The solution of the problem is investigated by proposing a modified log-barrier primal-dual interior/exterior point method with a quadratic test strategy and new search direction procedures. The quadratic test is proposed as an alternative strategy to the Cholesky procedure for calculating the positivity of the Hessian matrix of the problem.The new search directions investigated in the paper are determined by combining the search directions calculated in the predictor and corrector steps, respectively, and also by using information associated with the complementarity conditions. The method proposed is implemented in Matlab and applied to solving the reactive optimal power flow problem for 9 and 39-bus systems, as well as for the IEEE 14, 30, 57 and 118-bus test systems. The performance of the method with the proposed strategies for search directions is evaluated in terms of the number of iterations and computational times. The results are promising and allow the application of the present method with the proposed search strategies for solving problems of larger dimensions.
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Fernandes, Alexandre da Silva. "Representação de cenários de demanda e da função de produção hidrelétrica no planejamento da operação de sistemas hidrotérmicos a médio prazo." Universidade Federal de Juiz de Fora (UFJF), 2018. https://repositorio.ufjf.br/jspui/handle/ufjf/6802.
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O planejamento da operação do Sistema Interligado Nacional constitui-se uma tarefa de alta complexidade, seja pela quantidade acentuada de usinas hidrelétricas e termelétricas distribuídas nos quatro submercados interligados, ou pelas características marcantes da operação das hidrelétricas, no que diz respeito às incertezas dos cenários hidrológicos futuros e aos acoplamentos espacial e temporal. O objetivo deste planejamento é a determinação de uma política ótima de despacho das usinas do sistema de modo a minimizar o valor esperado dos custos operativos no horizonte considerado. Uma importante restrição do problema é o suprimento da demanda de energia elétrica, dado pela diferença entre a carga efetiva de cada submercado e a geração das usinas não simuladas, esta última composta pela energias alternativas (eólica, solar, biomassa), pequenas centrais hidrelétricas, entre outros. Entretanto, a crescente penetração da geração renovável, aliada às incertezas das fontes naturais como eólica e solar (pois dependem de fatores climáticos e por isso são imprevisíveis), contribui com a necessidade de representação da demanda em diversos cenários para um correto despacho das usinas e uma operação do sistema mais confiável. Sabendo que os modelos oficiais atuais tratam apenas as incertezas oriundas dos cenários hidrológicos, devido à dificuldade de implementação e alocação de memória na consideração de outras incertezas na Programação Dinâmica Dual Estocástica, o trabalho desenvolvido nesta dissertação propõe metodologias que incluem os diversos cenários de demanda, além de representar com maior detalhe a geração das hidrelétricas. Além disso, são propostos algoritmos de representação analítica da Função de Custo Imediato em sistemas isolados e com múltiplas áreas na busca por uma redução das dimensões do problema tratado. Finalmente, são realizados testes em sistemas tutorias e os resultados são analisados para avaliar as performances computacionais das metodologias propostas.
The operation schedulling of Brazilian System constitutes a task of high complexity, either due to the large number of hydro and thermal plants distributed in the four interconnected submarkets, or due to the outstanding characteristics of the hydro plants, with respect to the uncertainties in the hydrological scenarios future and due to spatial and temporal couplings. The objective of this planning is the determination of an optimal dispatch policy of plants that minimizes the expected value of the operating costs in the considered horizon. An important constraint is the supply of demand, which is obtained by the difference between the effective load of each submarket and the generation of non-simulated plants, composed of renewable energies (wind, solar, biomass), small hydropower plants, and others. However, the growing penetration of renewable generation, coupled with the uncertainties of natural sources such as wind and solar (because they depend on climatic factors and are therefore unpredictable), contributes to the need to represent demand in different scenarios for a correct dispatch of the plants and a more reliable system operation. Knowing that the current official models deal only with the uncertainties arising from the hydrological scenarios, due to the difficulty of implementation and memory allocation in the consideration of other uncertainties in Stochastic Dual Dynamic Programming, this work proposes methodologies that include the several scenarios demand, besides representing in greater detail the generation of hydroelectric plants. In addition, algorithms are proposed for analytical representation of the Immediate Cost Function in isolated systems with multiple areas in the search for a reduction of the dimensions of the problem. Finally, tests are performed on tutorial systems and the results are analyzed to evaluate the computational performances of the proposed methodologies.
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Paroda, Garcia Zeferino. "A modified augmented Lagrangian merit function, and Q-superlinear characterization results for primal-dual Quasi-Newton interior-point method for nonlinear programming." Thesis, 1997. http://hdl.handle.net/1911/19195.
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Two classes of primal-dual interior-point methods for nonlinear programming are studied. The first class corresponds to a path-following Newton method formulated in terms of the nonnegative variables rather than all primal and dual variables. The centrality condition is a relaxation of the perturbed Karush-Kuhn-Tucker condition and primarily forces feasibility in the constraints. In order to globalize the method using a linesearch strategy, a modified augmented Lagrangian merit function is defined in terms of the centrality condition. The second class is the Quasi-Newton interior-point methods. In this class the well known Boggs-Tolle-Wang characterization of Q-superlinear convergence for Quasi-Newton method for equality constrained optimization is extended. Critical issues in this extension are; the choice of the centering parameter, the choice of the steplength parameter, and the choice of the primary variables.
Книги з теми "Production function (dual and primal)"
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Silva, Elvira, Spiro E. Stefanou, and Alfons Oude Lansink. Dynamic Efficiency and Productivity Measurement. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780190919474.001.0001.
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The book takes on a systematic treatment of dynamic decision making and performance measurement. The analytical foundations of the dynamic production technology are introduced and developed in detail for several primal representations of the technology with an emphasis on dynamic directional distance functions. Dynamic cost minimization and dynamic profit maximization are developed for primal and dual representations of the dynamic technology. A dynamic production environment can be characterized as one where current production decisions impact future production possibilities. Consequently, the dynamic perspective of production relationships necessarily involves the close interplay between stock and flow elements in the transformation process and how current decisions impact the changes in future stocks. Stock elements in the production transformation process can involve physical elements that can be effectively employed in the transformation process, which can include the stock of technical knowledge and expertise available to the decision maker during the decision period. The dynamic generalization of concepts measuring the production structure (e.g., economies of scale, economies of scope, capacity utilization) and performance (e.g., allocative, scale and technical inefficiency, productivity) are developed from primal and dual perspectives. As an important source of productivity growth, production efficiency analysis is the subject of countless studies. Yet, theoretical and empirical studies focusing on production efficiency have ignored typically the time interdependence of production decisions and the adjustment paths of the firm over time. The empirical implementation of these production and performance measures is developed at length for both nonparametric and econometric approaches.
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Sheaff, Rod, and Jill Schofield. Inter-Organizational Networks in Health Care. Edited by Ewan Ferlie, Kathleen Montgomery, and Anne Reff Pedersen. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780198705109.013.29.
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Inter-organizational networks have proliferated in health systems, as has network research, but coherent explanations relating the varieties of health network to their respective structures, activities and outcomes remain lacking. Focusing on their core productive processes and their governance structures, this chapter contrasts care networks with program networks. It compares these concepts with findings from some primary research on NHS health networks during 2005–10, and notes some implications for network theory and research. NHS networks’ dense, flat structures reflect these networks’ dual function as both care and as program networks. These findings are relevant to the “integrated care” networks developing in many health systems. The development of these networks appears, partly, to be a workaround for the obstacles that market and quasi-market health systems place in the way of coordinating complex care across multiple separate providers.
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Lau, George F. South America—Andes. Edited by Timothy Insoll. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199675616.013.019.
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This chapter details major figurine developments in the ancient Andes and discusses new understandings based on figurine form, function, and imagery. Great formal diversity characterizes the long history of their use. The most active traditions occurred along the coast, while data from the highlands and eastern slopes are more limited. Certain regions, especially the north coast, show longevity in the use of figurines, especially in household, funerary, and offering contexts. Figurines were important for their role in embodying identity (e.g. gender, fertility, status) as well as alterity. Production and ritual embued them with divine powers and agency. Figurine use and imagery also show dual structures, often manifested in gendered pairs or object sets. Finally, Andean figurines were important for their interactions with other contexts and things, including other figurine-like items: they inspired their own small worlds of sociality.
Частини книг з теми "Production function (dual and primal)"
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Nesterov, Yurii. "The Primal-Dual Model of an Objective Function." In Lectures on Convex Optimization, 423–87. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91578-4_6.
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Kuroda, Yoshimi. "The Dual and Primal Rates of Technological Progress." In Production Structure and Productivity of Japanese Agriculture, 63–85. London: Palgrave Macmillan UK, 2013. http://dx.doi.org/10.1057/9781137287618_3.
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Ghami, Mohamed El. "Primal-Dual Algorithms for P ∗(κ) Linear Complementarity Problems Based on Kernel-Function with Trigonometric Barrier Term." In Optimization Theory, Decision Making, and Operations Research Applications, 331–49. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5134-1_24.
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Conn, Andrew R., Nicholas I. M. Gould, and Philippe L. Toint. "A primal-dual algorithm for minimizing a non-convex function subject to bound and linear equality constraints." In Applied Optimization, 15–49. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4757-3226-9_2.
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"Primal and Dual Approaches and Functional Forms: Production Function Estimation and Explanation." In Efficiency Issues in Transitional Economies, 97–117. Routledge, 2018. http://dx.doi.org/10.4324/9780429458279-17.
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Floudas, Christodoulos A. "Duality Theory." In Nonlinear and Mixed-Integer Optimization. Oxford University Press, 1995. http://dx.doi.org/10.1093/oso/9780195100563.003.0008.
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Nonlinear optimization problems have two different representations, the primal problem and the dual problem. The relation between the primal and the dual problem is provided by an elegant duality theory. This chapter presents the basics of duality theory. Section 4.1 discusses the primal problem and the perturbation function. Section 4.2 presents the dual problem. Section 4.3 discusses the weak and strong duality theorems, while section 4.4 discusses the duality gap. This section presents the formulation of the primal problem, the definition and properties of the perturbation function, the definition of stable primal problem, and the existence conditions of optimal multiplier vectors.
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Ye, Xugang, Shih-Ping Han, and Anhua Lin. "A Note on the Connection Between the Primal-Dual and the A* Algorithm." In Innovations in Information Systems for Business Functionality and Operations Management, 170–81. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0933-4.ch010.
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The primal-dual algorithm for linear programming is very effective for solving network flow problems. For the method to work, an initial feasible solution to the dual is required. In this article, we show that, for the shortest path problem in a positively weighted graph equipped with a consistent heuristic function, the primal-dual algorithm will become the well-known A* algorithm if a special initial feasible solution to the dual is chosen. We also show how the improvements of the dual objective are related to the A* iterations.
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Sun, Minghe. "Support Vector Machine Models for Classification." In Encyclopedia of Business Analytics and Optimization, 2395–409. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-5202-6.ch215.
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As machine learning techniques, support vector machines are quadratic programming models and are recent revolutionary development for classification analysis. Primal and dual formulations of support vector machine models for both two-class and multi-class classification are discussed. The dual formulations in high dimensional feature space using inner product kernels are emphasized. Nonlinear classification function or discriminant functions in high dimensional feature spaces can be constructed through the use of inner product kernels without actually mapping the data from the input space to the high dimensional feature spaces. Furthermore, the size of the dual formulation is independent of the dimension of the input space and independent of the kernels used. Two illustrative examples, one for two-class and the other for multi-class classification, are used to demonstrate the formulations of these SVM models.
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Silva, Elvira, Spiro E. Stefanou, and Alfons Oude Lansink. "Econometric Approaches." In Dynamic Efficiency and Productivity Measurement, 177–90. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780190919474.003.0007.
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Econometric approaches provide another avenue to implementing the frameworks and concepts of dynamic efficiency and productivity measurement. This chapter addresses both structural and reduced-form econometric approaches to estimating the dynamic directional distance function directly as well as to estimating the cost function that accommodates technical inefficiency. An application to a farm-level panel data set is presented that estimates the decomposition of dynamic cost inefficiency into technical and allocative inefficiency measures presented in Chapter 4 and then determines the components of primal and dual Luenberger total factor productivity change based on the elaboration of these concepts in Chapter 5. In addition to the discussion of empirical issues, this chapter provides an empirical illustration using micro-level data.
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Silva, Elvira, Spiro E. Stefanou, and Alfons Oude Lansink. "Dynamic Economic Decision Making." In Dynamic Efficiency and Productivity Measurement, 57–92. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780190919474.003.0004.
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This chapter presents dynamic optimization for economic decision making in the context of both dynamic cost minimization and dynamic profit maximization given different primal representations of the dynamic technology. The Bellman equation of dynamic programming serves as the analytical foundation for the duality between the production technology and the economic value function. The dynamic duality relationships in the form of intertemporal versions of Hotelling’s and Shephard’s lemmas are presented. The chapter concludes with the data envelopment perspective of the dynamic decision-making framework. Allowing the data to reveal the nature of the production technology, both the input and output quantities can be used to reveal the inner bound of the technology. Alternatively, the technological information can be recovered by exploiting the dynamic cost minimization behavior using input prices and input and output quantities, to reveal the outer bound of the input requirement set.
Тези доповідей конференцій з теми "Production function (dual and primal)"
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Huang, Zhiyi, and Anthony Kim. "Welfare Maximization with Production Costs: A Primal Dual Approach." In Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2014. http://dx.doi.org/10.1137/1.9781611973730.6.
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Chan, T.-H. Hubert, Kevin L. Chang, and Rajiv Raman. "An SDP primal-dual algorithm for approximating the Lovász-theta function." In 2009 IEEE International Symposium on Information Theory - ISIT. IEEE, 2009. http://dx.doi.org/10.1109/isit.2009.5205779.
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Cheng, Minhao, and Cho-Jui Hsieh. "Distributed Primal-Dual Optimization for Non-uniformly Distributed Data." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/280.
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Distributed primal-dual optimization has received many focuses in the past few years. In this framework, training samples are stored in multiple machines. At each round, all the machines conduct a sequence of updates based on their local data, and then the local updates are synchronized and merged to obtain the update to the global model. All the previous approaches merge the local updates by averaging all of them with a uniform weight. However, in many real world applications data are not uniformly distributed on each machine, so the uniform weight is inadequate to capture the heterogeneity of local updates. To resolve this issue, we propose a better way to merge local updates in the primal-dual optimization framework. Instead of using a single weight for all the local updates, we develop a computational efficient algorithm to automatically choose the optimal weights for each machine. Furthermore, we propose an efficient way to estimate the duality gap of the merged update by exploiting the structure of the objective function, and this leads to an efficient line search algorithm based on the reduction of duality gap. Combining these two ideas, our algorithm is much faster and more scalable than existing methods on real world problems.
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Wang, Guoqiang, and Yanqin Bai. "A Primal-Dual Interior-Point Algorithm for Convex Quadratic Optimization Based on a Parametric Kernel Function." In 2009 International Joint Conference on Computational Sciences and Optimization, CSO. IEEE, 2009. http://dx.doi.org/10.1109/cso.2009.155.
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Pu, Dingguo, and Youlin Shang. "Primal and Dual Variables for New QP-free Method without a Penalty Function and a Filter." In 2012 Fifth International Joint Conference on Computational Sciences and Optimization (CSO). IEEE, 2012. http://dx.doi.org/10.1109/cso.2012.71.
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Zhang, Xiong, Ji Zhou, Jun Yu, and Ju Cao. "A Primal-Dual Interior-Point QP Method and its Extension for Engineering Optimization." In ASME 1996 Design Engineering Technical Conferences and Computers in Engineering Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-detc/dac-1049.
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Abstract Presented in this paper is a primal-dual infeasible-interior-point quadratic programming (QP) algorithm and its extension for nonlinear programming that is suited for engineering design and structural optimization, where the number of variables are very large and function evaluations are computationally expensive. The computational experience in solving both test problems and optimal structural design problems using the algorithm demonstrated that the algorithm finds an approximate optimal solution in fewer iterations and function evaluations, the obtained solution usually is an interior feasible solution, and so the resulting method is very efficient and effective.
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Wang, Guoqiang, Baocun Wang, and Qingduan Fan. "An Infeasible Primal-Dual Interior-Point Algorithm for Linearly Constrained Convex Optimization Based on a Parametric Kernel Function." In 2009 International Joint Conference on Computational Sciences and Optimization, CSO. IEEE, 2009. http://dx.doi.org/10.1109/cso.2009.156.
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Yang, Xue-mei, Hua-li Zhao, and Guo-ling Hu. "Primal-Dual Interior-Point Methods for Second-Order Cone Complementarity Based on a New Class of Kernel Function." In 2010 Third International Joint Conference on Computational Science and Optimization. IEEE, 2010. http://dx.doi.org/10.1109/cso.2010.84.
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Wang, Guoqiang, and Fayan Wang. "A New Primal-Dual Interior-Point Algorithm for Convex Quadratic Symmetric Cone Optimization Based on a Parametric Kernel Function." In 2012 Fifth International Joint Conference on Computational Sciences and Optimization (CSO). IEEE, 2012. http://dx.doi.org/10.1109/cso.2012.52.
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Mohebbinia, Saeedeh, Stephen Peter Pennell, Raul Valdez, and Kiomars Eskandaridalvand. "Evaluation of Historical and Ongoing Double Displacement Process in Yates Field Unit." In SPE Improved Oil Recovery Conference. SPE, 2022. http://dx.doi.org/10.2118/209374-ms.
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Abstract Implementation of a second Double Displacement Process (DDP2) has been evaluated for Yates Field Unit (YFU). A DDP2 Demonstration Area Project has been designed to test DDP2 in a mature, high recovery area of the field. A detailed, geologically based reservoir description was used to build a simulation model for the DDP2 pilot area to study the DDP process and evaluate DDP2 performance. Initial saturations and relative permeability curves were generated based on a capillary pressure based Saturation Height Function (SHF) study. The fracture system was simulated using a hybrid dual porosity/permeability system. A 9-component equation of state (EOS) was used to model the YFU fluid properties. Capillary pressure of imbibition is used to capture the effect of hysteresis and oil trapping in the zones invaded by the aquifer during primary depletion. The simulation model has been tuned against historical performance since 1927, focusing on the first DDP process (DDP1) implemented over 1992-2000. Matching historical production/injection, field pressure and fluid contacts data were the history matching objectives. The DDP2 pilot project will include lowering 31 Horizontal Drain Hole (HDH) lateral completions by 25 feet to lower the contacts. The tuned model has been used to generate flow streams for different forecasting scenarios utilizing the DDP2 process. Forecast results show incremental oil recovery by lowering the contacts by 25 feet during the DDP2 phase. This paper presents a comprehensive study of YFU DDP1 process and evaluation of the second DDP process by a 3D numerical simulation model. The simulation model is used to improve understanding of the complex Gas-Oil Gravity Drainage (GOGD) and Gas Assisted Gravity Drainage (GAGD), and provide forecasts for the DDP2 process. Success of the pilot will result in extending the field life another 10-20 years.