Método previsor-corretor primal-dual de pontos interiores em problemas multiobjetivo de despacho econômico e ambiental

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Desenvolvimento de uma plataforma aberta de robô móvel para propósitos gerais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A contribuição de modelos utilizando uma abordagem modelo - código

In a world that is increasingly working with software, the need arises for effective approaches that encourage software reuse. The reuse practice must be aligned to a set of practices, procedures and methodologies that create a stable and high quality product. These questions produce new styles and approaches in the software engineering. In this way, this thesis aims to address concepts related to development and model-driven architecture. The model-driven approach provides significant aspects of the automated development, which helps it with produced models built in the specification phase. The definition of terms such as model, architecture and platform makes the focus becomes clearer, because for MDA and MDD is important to split between technical and business issues. Important processes are covered, so you can highlight the artifacts that are built into each stage of model-driven development. The stages of development: CSM, PIM, PSM and ISM, detailing the purpose of each phase in oriented models, making the end of each stage are gradually produced artifacts that may be specialized. The models are handled by different prospects for modeling, abstracting the concepts and building a set of details that portrays a specific scenario. This retraction can be a graphical or textual representation, however, in most cases is chosen a language modeling, for example, UML. In order to provide a practical view, this dissertation shows some tools that improve the construction of models and the code generate that assists in the development, keeping the documentation systemic. Finally, the paper presents a case study that refers to the theoretical aspects discussed throughout the dissertation, therefore it is expected that the architecture and the model-driven development may be able to explain important features to consider in software engineering

Artificial immune networks Copt-aiNet and Opt-aiNet applied to the reconfiguration problem of radial electrical distribution systems

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise numérica de um sistema integrado coletor solar/armazenador térmico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Three-Dimensional Semiautomatic Road Extraction From a High-Resolution Aerial Image by Dynamic-Programming Optimization in the Object Space

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Binary integer programming formulations for scheduling in market-driven foundries

This paper describes the development and solution of binary integer formulations for production scheduling problems in market-driven foundries. This industrial sector is comprised of small and mid-sized companies with little or no automation, working with diversified production, involving several different metal alloy specifications in small tailor-made product lots. The characteristics and constraints involved in a typical production environment at these industries challenge the formulation of mathematical programming models that can be computationally solved when considering real applications. However, despite the interest on the part of these industries in counting on effective methods for production scheduling, there are few studies available on the subject. The computational tests prove the robustness and feasibility of proposed models in situations analogous to those found in production scheduling at the analyzed industrial sector. (C) 2010 Elsevier Ltd. All rights reserved.

Allocation of protective devices in distribution circuits using nonlinear programming models and genetic algorithms

The optimized allocation of protective devices in strategic points of the circuit improves the quality of the energy supply and the system reliability index. This paper presents a nonlinear integer programming (NLIP) model with binary variables, to deal with the problem of protective device allocation in the main feeder and all branches of an overhead distribution circuit, to improve the reliability index and to provide customers with service of high quality and reliability. The constraints considered in the problem take into account technical and economical limitations, such as coordination problems of serial protective devices, available equipment, the importance of the feeder and the circuit topology. The use of genetic algorithms (GAs) is proposed to solve this problem, using a binary representation that does (1) or does not (0) show allocation of protective devices (reclosers, sectionalizers and fuses) in predefined points of the circuit. Results are presented for a real circuit (134 busses), with the possibility of protective device allocation in 29 points. Also the ability of the algorithm in finding good solutions while improving significantly the indicators of reliability is shown. (C) 2003 Elsevier B.V. All rights reserved.

Interior point algorithm for linear programming used in transmission network synthesis

This article presents a well-known interior point method (IPM) used to solve problems of linear programming that appear as sub-problems in the solution of the long-term transmission network expansion planning problem. The linear programming problem appears when the transportation model is used, and when there is the intention to solve the planning problem using a constructive heuristic algorithm (CHA), ora branch-and-bound algorithm. This paper shows the application of the IPM in a CHA. A good performance of the IPM was obtained, and then it can be used as tool inside algorithm, used to solve the planning problem. Illustrative tests are shown, using electrical systems known in the specialized literature. (C) 2005 Elsevier B.V. All rights reserved.

Determination of the optimal quantity of crop residues for energy in sugarcane crop management using linear programming in variety selection and planting strategy

The aim of this work was to present organizational models for optimizing the reduction of crop residue generated by the sugarcane culture. The first model consisted of the selection of varieties of sugarcane to be planted meeting the mill requirements and, at the same time, to minimize the quantity of residue produced. The second model discussed the use of residue to produce energy. This is related to the selection of variety and quantity to be planted, in order to meet the requirements of the mill, to reduce the quantity of residue, and to maximize as much as possible the energy production. The use of linear programming was proposed. The two models presented similar results in this study, and both may be used to define the varieties and areas to be cultivated. (C) 2001 Published by Elsevier B.V. Ltd.

Design and management optimization of trickle irrigation systems using non-linear programming

A non-linear model is presented which optimizes the lay-out, as well as the design and management of trickle irrigation systems, to achieve maximum net benefit. The model consists of an objective function that maximizes profit at the farm level, subject to appropriate geometric and hydraulic constraints. It can be applied to rectangular shaped fields, with uniform or zero slope. The software used is the Gams-Minos package. The basic inputs are the crop-water-production function, the cost function and cost of system components, and design variables. The main outputs are the annual net benefit and pipe diameters and lengths. To illustrate the capability of the model, a sensitivity analysis of the annual net benefit for a citrus field is evaluated with respect to irrigated area, ground slope, micro-sprinkler discharge and shape of the field. The sensitivity analysis suggests that the greatest benefit is obtained with the smallest microsprinkler discharge, the greatest area, a square field and zero ground slope. The costs of the investment and energy are the components of the objective function that had the greatest effect in the 120 situations evaluated. (C) 1996 Academic Press Limited

The Neuropsychiatric Inventory-Clinician rating scale (NPI-C): Reliability and validity of a revised assessment of neuropsychiatric symptoms in dementia

Background: Neuropsychiatric symptoms (NPS) affect almost all patients with dementia and are a major focus of study and treatment. Accurate assessment of NPS through valid, sensitive and reliable measures is crucial. Although current NPS measures have many strengths, they also have some limitations (e.g. acquisition of data is limited to informants or caregivers as respondents, limited depth of items specific to moderate dementia). Therefore, we developed a revised version of the NPI, known as the NPI-C. The NPI-C includes expanded domains and items, and a clinician-rating methodology. This study evaluated the reliability and convergent validity of the NPI-C at ten international sites (seven languages). Methods: Face validity for 78 new items was obtained through a Delphi panel. A total of 128 dyads (caregivers/patients) from three severity categories of dementia (mild = 58, moderate = 49, severe = 21) were interviewed separately by two trained raters using two rating methods: the original NPI interview and a clinician-rated method. Rater 1 also administered four additional, established measures: the Apathy Evaluation Scale, the Brief Psychiatric Rating Scale, the Cohen-Mansfield Agitation Index, and the Cornell Scale for Depression in Dementia. Intraclass correlations were used to determine inter-rater reliability. Pearson correlations between the four relevant NPI-C domains and their corresponding outside measures were used for convergent validity. Results: Inter-rater reliability was strong for most items. Convergent validity was moderate (apathy and agitation) to strong (hallucinations and delusions; agitation and aberrant vocalization; and depression) for clinician ratings in NPI-C domains. Conclusion: Overall, the NPI-C shows promise as a versatile tool which can accurately measure NPS and which uses a uniform scale system to facilitate data comparisons across studies. Copyright © 2010 International Psychogeriatric Association.

A multi-objective programming approach for the optimal operation of distributed generation considering uncertainty

Due to the renewed interest in distributed generation (DG), the number of DG units incorporated in distribution systems has been rapidly increasing in the past few years. This situation requires new analysis tools for understanding system performance, and taking advantage of the potential benefits of DG. This paper presents an evolutionary multi-objective programming approach to determine the optimal operation of DG in distribution systems. The objectives are the minimization of the system power losses and operation cost of the DG units. The proposed approach also considers the inherent stochasticity of DG technologies powered by renewable resources. Some tests were carried out on the IEEE 34 bus distribution test system showing the robustness and applicability of the proposed methodology. © 2011 IEEE.

Optimal reactive power dispatch using stochastic chance-constrained programming

Deterministic Optimal Reactive Power Dispatch problem has been extensively studied, such that the demand power and the availability of shunt reactive power compensators are known and fixed. Give this background, a two-stage stochastic optimization model is first formulated under the presumption that the load demand can be modeled as specified random parameters. A second stochastic chance-constrained model is presented considering uncertainty on the demand and the equivalent availability of shunt reactive power compensators. Simulations on six-bus and 30-bus test systems are used to illustrate the validity and essential features of the proposed models. This simulations shows that the proposed models can prevent to the power system operator about of the deficit of reactive power in the power system and suggest that shunt reactive sourses must be dispatched against the unavailability of any reactive source. © 2012 IEEE.

A mixed-integer linear programming approach for optimal type, size and allocation of distributed generation in radial distribution systems

This paper presents a mixed-integer linear programming approach to solving the problem of optimal type, size and allocation of distributed generators (DGs) in radial distribution systems. In the proposed formulation, (a) the steady-state operation of the radial distribution system, considering different load levels, is modeled through linear expressions; (b) different types of DGs are represented by their capability curves; (c) the short-circuit current capacity of the circuits is modeled through linear expressions; and (d) different topologies of the radial distribution system are considered. The objective function minimizes the annualized investment and operation costs. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique.© 2012 Elsevier B.V. All rights reserved.