947 resultados para Transport network optimization
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Dissertação de natureza científica realizada para obtenção do grau de Mestre em Engenharia Informática e de Computadores
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Mestrado em Radiações Aplicadas às Tecnologias da Saúde - Área de especialização: Imagem Digital por Radiação X.
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As it is well known, competitive electricity markets require new computing tools for power companies that operate in retail markets in order to enhance the management of its energy resources. During the last years there has been an increase of the renewable penetration into the micro-generation which begins to co-exist with the other existing power generation, giving rise to a new type of consumers. This paper develops a methodology to be applied to the management of the all the aggregators. The aggregator establishes bilateral contracts with its clients where the energy purchased and selling conditions are negotiated not only in terms of prices but also for other conditions that allow more flexibility in the way generation and consumption is addressed. The aggregator agent needs a tool to support the decision making in order to compose and select its customers' portfolio in an optimal way, for a given level of profitability and risk.
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In real optimization problems, usually the analytical expression of the objective function is not known, nor its derivatives, or they are complex. In these cases it becomes essential to use optimization methods where the calculation of the derivatives, or the verification of their existence, is not necessary: the Direct Search Methods or Derivative-free Methods are one solution. When the problem has constraints, penalty functions are often used. Unfortunately the choice of the penalty parameters is, frequently, very difficult, because most strategies for choosing it are heuristics strategies. As an alternative to penalty function appeared the filter methods. A filter algorithm introduces a function that aggregates the constrained violations and constructs a biobjective problem. In this problem the step is accepted if it either reduces the objective function or the constrained violation. This implies that the filter methods are less parameter dependent than a penalty function. In this work, we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of the simplex method and filter methods. This method does not compute or approximate any derivatives, penalty constants or Lagrange multipliers. The basic idea of simplex filter algorithm is to construct an initial simplex and use the simplex to drive the search. We illustrate the behavior of our algorithm through some examples. The proposed methods were implemented in Java.
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The filter method is a technique for solving nonlinear programming problems. The filter algorithm has two phases in each iteration. The first one reduces a measure of infeasibility, while in the second the objective function value is reduced. In real optimization problems, usually the objective function is not differentiable or its derivatives are unknown. In these cases it becomes essential to use optimization methods where the calculation of the derivatives or the verification of their existence is not necessary: direct search methods or derivative-free methods are examples of such techniques. In this work we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of simplex and filter methods. This method neither computes nor approximates derivatives, penalty constants or Lagrange multipliers.
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In this work we solve Mathematical Programs with Complementarity Constraints using the hyperbolic smoothing strategy. Under this approach, the complementarity condition is relaxed through the use of the hyperbolic smoothing function, involving a positive parameter that can be decreased to zero. An iterative algorithm is implemented in MATLAB language and a set of AMPL problems from MacMPEC database were tested.
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In this paper a solution to an highly constrained and non-convex economical dispatch (ED) problem with a meta-heuristic technique named Sensing Cloud Optimization (SCO) is presented. The proposed meta-heuristic is based on a cloud of particles whose central point represents the objective function value and the remaining particles act as sensors "to fill" the search space and "guide" the central particle so it moves into the best direction. To demonstrate its performance, a case study with multi-fuel units and valve- point effects is presented.
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Mestrado em Engenharia Electrotécnica e de Computadores
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This paper deals with the coupled effect of temperature and silica fume addition on rheological, mechanical behaviour and porosity of grouts based on CEMI 42.5R, proportioned with a polycarboxylate-based high range water reducer. Preliminary tests were conducted to focus on the grout best able to fill a fibrous network since the goal of this study was to develop an optimized grout able to be injected in a mat of steel fibers for concrete strengthening. The grout composition was developed based on criteria for fresh state and hardened state properties. For a CEMI 42.5R based grout different high range water reducer dosages (0%, 0.2%, 0.4%, 0.5%, 0.7%) and silica fume (SF) dosages (0%, 2%, 4%) were tested (as replacement of cement by mass). Rheological measurements were used to investigate the effect of polycarboxylates (PCEs) and SF dosage on grout properties, particularly its workability loss, as the mix was to be injected in a matrix of steel fibers for concrete jacketing. The workability behaviour was characterized by the rheological parameters yield stress and plastic viscosity (for different grout temperatures and resting times), as well as the procedures of mini slump cone and funnel flow time. Then, further development focused only on the best grout compositions. The cement substitution by 2% of SF exhibited the best overall behaviour and was considered as the most promising compared to the others compositions tested. Concerning the fresh state analysis, a significant workability loss was detected if grout temperature increased above 35 degrees C. Below this temperature the grout presented a self-levelling behaviour and a life time equal to 45 min. In the hardened state, silica fumes increased not only the grout's porosity but also the grout's compressive strength at later ages, since the pozzolanic contribution to the compressive strength does not occur until 28 d and beyond. (C) 2012 Elsevier Ltd. All rights reserved.
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Mestrado em Engenharia Informática
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Mestrado em Engenharia Informática
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Mestrado em Engenharia Electrotécnica e de Computadores
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Mestrado em Engenharia Electrotécnica e de Computadores
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The Bologna Process aimed to build a European Higher Education Area promoting student's mobility. The adoption of Bologna Declaration directives requires a self management distributed approach to deal with student's mobility, allowing frequent updates in institutions rules or legislation. This paper suggests a computational system architecture, which follows a social network design. A set of structured annotations is proposed in order to organize the user's information. For instance, when the user is a student its annotations are organized into an academic record. The academic record data is used to discover interests, namely mobility interests, among students that belongs the academic network. These ideas have been applied into a demonstrator that includes a mobility simulator to compare and show the student's academic evolution.
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We have developed a new method for single-drop microextraction (SDME) for the preconcentration of organochlorine pesticides (OCP) from complex matrices. It is based on the use of a silicone ring at the tip of the syringe. A 5 μL drop of n-hexane is applied to an aqueous extract containing the OCP and found to be adequate to preconcentrate the OCPs prior to analysis by GC in combination with tandem mass spectrometry. Fourteen OCP were determined using this technique in combination with programmable temperature vaporization. It is shown to have many advantages over traditional split/splitless injection. The effects of kind of organic solvent, exposure time, agitation and organic drop volume were optimized. Relative recoveries range from 59 to 117 %, with repeatabilities of <15 % (coefficient of variation) were achieved. The limits of detection range from 0.002 to 0.150 μg kg−1. The method was applied to the preconcentration of OCPs in fresh strawberry, strawberry jam, and soil.