55 resultados para GAMS


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The objective of this work was to evaluate different concentrations of nutritional solution in the hydroponic cultivation of Viola x wittrockiana Gams. The experiment was conducted in DFT hydroponic system, in a completely randomized design with a 5×4 factorial scheme and five nutrient solution concentrations (50, 75, 100, 125 and 150%), four evaluation periods with three replications of three plants for each treatment. Plant height, root length, number of leaves, flowers and floral buttons; fresh and dry weight of shoot and root were determined. The results were submitted to variance analysis, Tukey's test for evaluation periods and regression analysis for nutrient solution. A decrease in the development of the shoot and root was observed with an increase of the number of cultivation days; the greatest number of floral buttons occurred in the third week of cultivation. A reduction in the plant height, root system length, the number of leaves and the fresh and dry weight of shoot was observed generally with the increase of nutrient solution concentration.

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Global competitiveness has been increased significantly in the last decade and, as consequence, companies are always looking for developing better processes in supply chain operations in order to maintain their competitive costs and keep themselves in the business. Logistics operations represent a large part of the product's final cost. Transportation can represent more than fifty percent of final cost sometimes. The solutions for cutting and packing problems consist in simple and low investment actions, as enhancing the arrangement of the transported load in order to decrease both material and room wastes. As per the presented reasons, the objective of this paper is to show and analyze a real application of a mathematical model to solve a manufacturer pallet-loading problem, comparing results from the model execution and the solution proposed by the company studied. This study will not only find the best arrangement to load pallets (which will optimize storage and transportation process), but also to check the effectiveness of existing modeling in the literature. For this study a computational package was used, which consists of a modeling language GAMS with the CPLEX optimization solver and two other existing software in the market, all of them indicating that an accurate mathematical model for solving this kind of problem in a two-dimensional approach is difficult to be found, in addition to a long execution time. However, the study and the software utilization indicate that the problem would be easily solved by heuristics in a shorter execution time

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Global competitiveness has been increased significantly in the last decade and, as consequence, companies are always looking for developing better processes in supply chain operations in order to maintain their competitive costs and keep themselves in the business. Logistics operations represent a large part of the product's final cost. Transportation can represent more than fifty percent of final cost sometimes. The solutions for cutting and packing problems consist in simple and low investment actions, as enhancing the arrangement of the transported load in order to decrease both material and room wastes. As per the presented reasons, the objective of this paper is to show and analyze a real application of a mathematical model to solve a manufacturer pallet-loading problem, comparing results from the model execution and the solution proposed by the company studied. This study will not only find the best arrangement to load pallets (which will optimize storage and transportation process), but also to check the effectiveness of existing modeling in the literature. For this study a computational package was used, which consists of a modeling language GAMS with the CPLEX optimization solver and two other existing software in the market, all of them indicating that an accurate mathematical model for solving this kind of problem in a two-dimensional approach is difficult to be found, in addition to a long execution time. However, the study and the software utilization indicate that the problem would be easily solved by heuristics in a shorter execution time

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This paper presents the development of a mathematical model to optimize the management and operation of the Brazilian hydrothermal system. The system consists of a large set of individual hydropower plants and a set of aggregated thermal plants. The energy generated in the system is interconnected by a transmission network so it can be transmitted to centers of consumption throughout the country. The optimization model offered is capable of handling different types of constraints, such as interbasin water transfers, water supply for various purposes, and environmental requirements. Its overall objective is to produce energy to meet the country's demand at a minimum cost. Called HIDROTERM, the model integrates a database with basic hydrological and technical information to run the optimization model, and provides an interface to manage the input and output data. The optimization model uses the General Algebraic Modeling System (GAMS) package and can invoke different linear as well as nonlinear programming solvers. The optimization model was applied to the Brazilian hydrothermal system, one of the largest in the world. The system is divided into four subsystems with 127 active hydropower plants. Preliminary results under different scenarios of inflow, demand, and installed capacity demonstrate the efficiency and utility of the model. From this and other case studies in Brazil, the results indicate that the methodology developed is suitable to different applications, such as planning operation, capacity expansion, and operational rule studies, and trade-off analysis among multiple water users. DOI: 10.1061/(ASCE)WR.1943-5452.0000149. (C) 2012 American Society of Civil Engineers.

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The objective of this report is to study distributed (decentralized) three phase optimal power flow (OPF) problem in unbalanced power distribution networks. A full three phase representation of the distribution networks is considered to account for the highly unbalance state of the distribution networks. All distribution network’s series/shunt components, and load types/combinations had been modeled on commercial version of General Algebraic Modeling System (GAMS), the high-level modeling system for mathematical programming and optimization. The OPF problem has been successfully implemented and solved in a centralized approach and distributed approach, where the objective is to minimize the active power losses in the entire system. The study was implemented on the IEEE-37 Node Test Feeder. A detailed discussion of all problem sides and aspects starting from the basics has been provided in this study. Full simulation results have been provided at the end of the report.

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Positive allosteric modulators of GABAA receptors (GAMs) acting at specific subtypes of GABAA receptors effectively restore compromised spinal pain control in rodents. Studies addressing a similar antihyperalgesic effect in humans are sparse and are hampered by sedative effects of nonselective GAMs available for use in humans. We present results from a randomized controlled double-blind crossover study in 25 healthy volunteers, which addressed potential antihyperalgesic actions of clobazam (CBZ) and clonazepam (CLN) at mildly sedating equianticonvulsive doses. Clobazam was chosen because of its relatively low sedative properties and CLN because of its use in neuropathic pain. Tolterodine (TLT) was used as an active placebo. The primary outcome parameter was a change in the area of cutaneous UVB irradiation-induced secondary hyperalgesia (ASH), which was monitored for 8 hours after drug application. Sedative effects were assessed in parallel to antihyperalgesia. Compared with TLT, recovery from hyperalgesia was significantly faster in the CBZ and CLN groups (P = 0.009). At the time point of maximum effect, the rate of recovery from hyperalgesia was accelerated by CBZ and CLN, relative to placebo by 15.7% (95% confidence interval [CI] 0.8-30.5), P = 0.040, and 28.6% (95% CI 4.5-52.6), P = 0.022, respectively. Active compounds induced stronger sedation than placebo, but these differences disappeared 8 hours after drug application. We demonstrate here that GAMs effectively reduce central sensitization in healthy volunteers. These results provide proof-of-principle evidence supporting efficacy of GAMs as antihyperalgesic agents in humans and should stimulate further research on compounds with improved subtype specificity.

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Many studies have shown relationships between air pollution and the rate of hospital admissions for asthma. A few studies have controlled for age-specific effects by adding separate smoothing functions for each age group. However, it has not yet been reported whether air pollution effects are significantly different for different age groups. This lack of information is the motivation for this study, which tests the hypothesis that air pollution effects on asthmatic hospital admissions are significantly different by age groups. Each air pollutant's effect on asthmatic hospital admissions by age groups was estimated separately. In this study, daily time-series data for hospital admission rates from seven cities in Korea from June 1999 through 2003 were analyzed. The outcome variable, daily hospital admission rates for asthma, was related to five air pollutants which were used as the independent variables, namely particulate matter <10 micrometers (μm) in aerodynamic diameter (PM10), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), and sulfur dioxide (SO2). Meteorological variables were considered as confounders. Admission data were divided into three age groups: children (<15 years of age), adults (ages 15-64), and elderly (≥ 65 years of age). The adult age group was considered to be the reference group for each city. In order to estimate age-specific air pollution effects, the analysis was separated into two stages. In the first stage, Generalized Additive Models (GAMs) with cubic spline for smoothing were applied to estimate the age-city-specific air pollution effects on asthmatic hospital admission rates by city and age group. In the second stage, the Bayesian Hierarchical Model with non-informative prior which has large variance was used to combine city-specific effects by age groups. The hypothesis test showed that the effects of PM10, CO and NO2 were significantly different by age groups. Assuming that the air pollution effect for adults is zero as a reference, age-specific air pollution effects were: -0.00154 (95% confidence interval(CI)= (-0.0030,-0.0001)) for children and 0.00126 (95% CI = (0.0006, 0.0019)) for the elderly for PM 10; -0.0195 (95% CI = (-0.0386,-0.0004)) for children for CO; and 0.00494 (95% CI = (0.0028, 0.0071)) for the elderly for NO2. Relative rates (RRs) were 1.008 (95% CI = (1.000-1.017)) in adults and 1.021 (95% CI = (1.012-1.030)) in the elderly for every 10 μg/m3 increase of PM10 , 1.019 (95% CI = (1.005-1.033)) in adults and 1.022 (95% CI = (1.012-1.033)) in the elderly for every 0.1 part per million (ppm) increase of CO; 1.006 (95%CI = (1.002-1.009)) and 1.019 (95%CI = (1.007-1.032)) in the elderly for every 1 part per billion (ppb) increase of NO2 and SO2, respectively. Asthma hospital admissions were significantly increased for PM10 and CO in adults, and for PM10, CO, NO2 and SO2 in the elderly.^

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Secchi depth is a measure of water transparency. In the Baltic Sea region, Secchi depth maps are used to assess eutrophication and as input for habitat models. Due to their spatial and temporal coverage, satellite data would be the most suitable data source for such maps. But the Baltic Sea's optical properties are so different from the open ocean that globally calibrated standard models suffer from large errors. Regional predictive models that take the Baltic Sea's special optical properties into account are thus needed. This paper tests how accurately generalized linear models (GLMs) and generalized additive models (GAMs) with MODIS/Aqua and auxiliary data as inputs can predict Secchi depth at a regional scale. It uses cross-validation to test the prediction accuracy of hundreds of GAMs and GLMs with up to 5 input variables. A GAM with 3 input variables (chlorophyll a, remote sensing reflectance at 678 nm, and long-term mean salinity) made the most accurate predictions. Tested against field observations not used for model selection and calibration, the best model's mean absolute error (MAE) for daily predictions was 1.07 m (22%), more than 50% lower than for other publicly available Baltic Sea Secchi depth maps. The MAE for predicting monthly averages was 0.86 m (15%). Thus, the proposed model selection process was able to find a regional model with good prediction accuracy. It could be useful to find predictive models for environmental variables other than Secchi depth, using data from other satellite sensors, and for other regions where non-standard remote sensing models are needed for prediction and mapping. Annual and monthly mean Secchi depth maps for 2003-2012 come with this paper as Supplementary materials.

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This paper explains how the Armington-Krugman-Melitz supermodel developed by Dixon and Rimmer can be parameterized, and demonstrates that only two kinds of additional information are required in order to extend a standard trade model to include Melitz-type monopolistic competition and heterogeneous firms. Further, it is shown how specifying too much additional information leads to violations of the model constraints, necessitating adjustment and reconciliation of the data. Once a Melitz-type model is parameterized, a Krugman-type model can also be parameterized using the calibrated values in the Melitz-type model without any additional data. Sample code for the General Algebraic Modeling System (GAMS) has also been prepared to promote the innovative supermodel in the AGE community.

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Rising water demands are difficult to meet in many regions of the world. In consequence, under meteorological adverse conditions, big economic losses in agriculture can take place. This paper aims to analyze the variability of water shortage in an irrigation district and the effect on farmer?s income. A probabilistic analysis of water availability for agriculture in the irrigation district is performed, through a supply-system simulation approach, considering stochastically generated series of stream-flows. Net margins associated to crop production are as well estimated depending on final water allocations. Net margins are calculated considering either single-crop farming, either a polyculture system. In a polyculture system, crop distribution and water redistribution are calculated through an optimization approach using the General Algebraic Modeling System (GAMS) for several scenarios of irrigation water availability. Expected net margins are obtained by crop and for the optimal crop and water distribution. The maximum expected margins are obtained for the optimal crop combination, followed by the alfalfa monoculture, maize, rice, wheat and finally barley. Water is distributed as follows, from biggest to smallest allocation: rice, alfalfa, maize, wheat and barley.

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The relationship of the important cellulase producing asexual fungus Trichoderma reesei to its putative teleomorphic (sexual) ancestor Hypocrea jecorina and other species of the Trichoderma sect. Longibrachiatum was studied by PCR-fingerprinting and sequence analyses of the nuclear ribosomal DNA region containing the internal transcribed spacers (ITS-1 and ITS-2) and the 5.8S rRNA gene. The differences in the corresponding ITS sequences allowed a grouping of anamorphic (asexual) species of Trichoderma sect. Longibrachiatum into Trichoderma longibrachiatum, Trichoderma pseudokoningii, and Trichoderma reesei. The sexual species Hypocrea schweinitzii and H. jecorina were also clearly separated from each other. H. jecorina and T. reesei exhibited identical sequences, suggesting close relatedness or even species identity. Intraspecific and interspecific variation in the PCR-fingerprinting patterns supported the differentiation of species based on ITS sequences, the grouping of the strains, and the assignment of these strains to individual species. The variations between T. reesei and H. jecorina were at the same order of magnitude as found between all strains of H. jecorina, but much lower than the observed interspecific variations. Identical ITS sequences and the high similarity of PCR-fingerprinting patterns indicate a very close relationship between T. reesei and H. jecorina, whereas differences of the ITS sequences and the PCR-fingerprinting patterns show a clear phylogenetic distance between T. reesei/H. jecorina and T. longibrachiatum. T. reesei is considered to be an asexual, clonal line derived from a population of the tropical ascomycete H. jecorina.

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Degradable matrices containing expression plasmid DNA [gene-activated matrices (GAMs)] were implanted into segmental gaps created in the adult rat femur. Implantation of GAMs containing beta-galactosidase or luciferase plasmids led to DNA uptake and functional enzyme expression by repair cells (granulation tissue) growing into the gap. Implantation of a GAM containing either a bone morphogenetic protein-4 plasmid or a plasmid coding for a fragment of parathyroid hormone (amino acids 1-34) resulted in a biological response of new bone filling the gap. Finally, implantation of a two-plasmid GAM encoding bone morphogenetic protein-4 and the parathyroid hormone fragment, which act synergistically in vitro, caused new bone to form faster than with either factor alone. These studies demonstrate for the first time that repair cells (fibroblasts) in bone can be genetically manipulated in vivo. While serving as a useful tool to study the biology of repair fibroblasts and the wound healing response, the GAM technology may also have wide therapeutic utility.

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O problema de Planejamento da Expansão de Sistemas de Distribuição (PESD) visa determinar diretrizes para a expansão da rede considerando a crescente demanda dos consumidores. Nesse contexto, as empresas distribuidoras de energia elétrica têm o papel de propor ações no sistema de distribuição com o intuito de adequar o fornecimento da energia aos padrões exigidos pelos órgãos reguladores. Tradicionalmente considera-se apenas a minimização do custo global de investimento de planos de expansão, negligenciando-se questões de confiabilidade e robustez do sistema. Como consequência, os planos de expansão obtidos levam o sistema de distribuição a configurações que são vulneráveis a elevados cortes de carga na ocorrência de contingências na rede. Este trabalho busca a elaboração de uma metodologia para inserir questões de confiabilidade e risco ao problema PESD tradicional, com o intuito de escolher planos de expansão que maximizem a robustez da rede e, consequentemente, atenuar os danos causados pelas contingências no sistema. Formulou-se um modelo multiobjetivo do problema PESD em que se minimizam dois objetivos: o custo global (que incorpora custo de investimento, custo de manutenção, custo de operação e custo de produção de energia) e o risco de implantação de planos de expansão. Para ambos os objetivos, são formulados modelos lineares inteiros mistos que são resolvidos utilizando o solver CPLEX através do software GAMS. Para administrar a busca por soluções ótimas, optou-se por programar em linguagem C++ dois Algoritmos Evolutivos: Non-dominated Sorting Genetic Algorithm-2 (NSGA2) e Strength Pareto Evolutionary Algorithm-2 (SPEA2). Esses algoritmos mostraram-se eficazes nessa busca, o que foi constatado através de simulações do planejamento da expansão de dois sistemas testes adaptados da literatura. O conjunto de soluções encontradas nas simulações contém planos de expansão com diferentes níveis de custo global e de risco de implantação, destacando a diversidade das soluções propostas. Algumas dessas topologias são ilustradas para se evidenciar suas diferenças.

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O objetivo do presente trabalho é a investigação e o desenvolvimento de estratégias de otimização contínua e discreta para problemas de Fluxo de Potência Ótimo (FPO), onde existe a necessidade de se considerar as variáveis de controle associadas aos taps de transformadores em-fase e chaveamentos de bancos de capacitores e reatores shunt como variáveis discretas e existe a necessidade da limitação, e/ou até mesmo a minimização do número de ações de controle. Neste trabalho, o problema de FPO será abordado por meio de três estratégias. Na primeira proposta, o problema de FPO é modelado como um problema de Programação Não Linear com Variáveis Contínuas e Discretas (PNLCD) para a minimização de perdas ativas na transmissão; são propostas três abordagens utilizando funções de discretização para o tratamento das variáveis discretas. Na segunda proposta, considera-se que o problema de FPO, com os taps de transformadores discretos e bancos de capacitores e reatores shunts fixos, possui uma limitação no número de ações de controles; variáveis binárias associadas ao número de ações de controles são tratadas por uma função quadrática. Na terceira proposta, o problema de FPO é modelado como um problema de Otimização Multiobjetivo. O método da soma ponderada e o método ε-restrito são utilizados para modificar os problemas multiobjetivos propostos em problemas mono-objetivos. As variáveis binárias associadas às ações de controles são tratadas por duas funções, uma sigmoidal e uma polinomial. Para verificar a eficácia e a robustez dos modelos e algoritmos desenvolvidos serão realizados testes com os sistemas elétricos IEEE de 14, 30, 57, 118 e 300 barras. Todos os algoritmos e modelos foram implementados em General Algebraic Modeling System (GAMS) e os solvers CONOPT, IPOPT, KNITRO e DICOPT foram utilizados na resolução dos problemas. Os resultados obtidos confirmam que as estratégias de discretização são eficientes e as propostas de modelagem para variáveis binárias permitem encontrar soluções factíveis para os problemas envolvendo as ações de controles enquanto os solvers DICOPT e KNITRO utilizados para modelar variáveis binárias não encontram soluções.

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The optimal integration of work and its interaction with heat can represent large energy savings in industrial plants. This paper introduces a new optimization model for the simultaneous synthesis of work exchange networks (WENs), with heat integration for the optimal pressure recovery of process gaseous streams. The proposed approach for the WEN synthesis is analogous to the well-known problem of synthesis of heat exchanger networks (HENs). Thus, there is work exchange between high-pressure (HP) and low-pressure (LP) streams, achieved by pressure manipulation equipment running on common axes. The model allows the use of several units of single-shaft-turbine-compressor (SSTC), as well as stand-alone compressors, turbines and valves. Helper motors and generators are used to respond to any demand and excess of energy. Moreover, between the WEN stages the streams are sent to the HEN to promote thermal recovery, aiming to enhance the work integration. A multi-stage superstructure is proposed to represent the process. The WEN superstructure is optimized in a mixed-integer nonlinear programming (MINLP) formulation and solved with the GAMS software, with the goal of minimizing the total annualized cost. Three examples are conducted to verify the accuracy of the proposed method. In all case studies, the heat integration between WEN stages is essential to improve the pressure recovery, and to reduce the total costs involved in the process.