892 resultados para Nonlinear Programming


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Constrained and unconstrained Nonlinear Optimization Problems often appear in many engineering areas. In some of these cases it is not possible to use derivative based optimization methods because the objective function is not known or it is too complex or the objective function is non-smooth. In these cases derivative based methods cannot be used and Direct Search Methods might be the most suitable optimization methods. An Application Programming Interface (API) including some of these methods was implemented using Java Technology. This API can be accessed either by applications running in the same computer where it is installed or, it can be remotely accessed through a LAN or the Internet, using webservices. From the engineering point of view, the information needed from the API is the solution for the provided problem. On the other hand, from the optimization methods researchers’ point of view, not only the solution for the problem is needed. Also additional information about the iterative process is useful, such as: the number of iterations; the value of the solution at each iteration; the stopping criteria, etc. In this paper are presented the features added to the API to allow users to access to the iterative process data.

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Solving systems of nonlinear equations is a very important task since the problems emerge mostly through the mathematical modelling of real problems that arise naturally in many branches of engineering and in the physical sciences. The problem can be naturally reformulated as a global optimization problem. In this paper, we show that a self-adaptive combination of a metaheuristic with a classical local search method is able to converge to some difficult problems that are not solved by Newton-type methods.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Informática.

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Computational Intelligence (CI) includes four main areas: Evolutionary Computation (genetic algorithms and genetic programming), Swarm Intelligence, Fuzzy Systems and Neural Networks. This article shows how CI techniques overpass the strict limits of Artificial Intelligence field and can help solving real problems from distinct engineering areas: Mechanical, Computer Science and Electrical Engineering.

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Solving systems of nonlinear equations is a problem of particular importance since they emerge through the mathematical modeling of real problems that arise naturally in many branches of engineering and in the physical sciences. The problem can be naturally reformulated as a global optimization problem. In this paper, we show that a metaheuristic, called Directed Tabu Search (DTS) [16], is able to converge to the solutions of a set of problems for which the fsolve function of MATLAB® failed to converge. We also show the effect of the dimension of the problem in the performance of the DTS.

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We study some properties of the monotone solutions of the boundary value problem (p(u'))' - cu' + f(u) = 0, u(-infinity) = 0, u(+infinity) = 1, where f is a continuous function, positive in (0, 1) and taking the value zero at 0 and 1, and P may be an increasing homeomorphism of (0, 1) or (0, +infinity) onto [0, +infinity). This problem arises when we look for travelling waves for the reaction diffusion equation partial derivative u/partial derivative t = partial derivative/partial derivative x [p(partial derivative u/partial derivative x)] + f(u) with the parameter c representing the wave speed. A possible model for the nonlinear diffusion is the relativistic curvature operator p(nu)= nu/root 1-nu(2). The same ideas apply when P is given by the one- dimensional p- Laplacian P(v) = |v|(p-2)v. In this case, an advection term is also considered. We show that, as for the classical Fisher- Kolmogorov- Petrovski- Piskounov equations, there is an interval of admissible speeds c and we give characterisations of the critical speed c. We also present some examples of exact solutions. (C) 2014 Elsevier Inc. All rights reserved.

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This paper studies the describing function (DF) of systems consisting in a mass subjected to nonlinear friction. The friction force is composed in three components namely, the viscous, the Coulomb and the static forces. The system dynamics is analyzed in the DF perspective revealing a fractional-order behaviour. The reliability of the DF method is evaluated through the signal harmonic content and the limit cycle prediction.

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A stochastic programming approach is proposed in this paper for the development of offering strategies for a wind power producer. The optimization model is characterized by making the analysis of several scenarios and treating simultaneously two kinds of uncertainty: wind power and electricity market prices. The approach developed allows evaluating alternative production and offers strategies to submit to the electricity market with the ultimate goal of maximizing profits. An innovative comparative study is provided, where the imbalances are treated differently. Also, an application to two new realistic case studies is presented. Finally, conclusions are duly drawn.

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The development of fractional-order controllers is currently one of the most promising fields of research. However, most of the work in this area addresses the case of linear systems. This paper reports on the analysis of fractional-order control of nonlinear systems. The performance of discrete fractional-order PID controllers in the presence of several nonlinearities is discussed. Some results are provided that indicate the superior robustness of such algorithms.

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The present generation of eLearning platforms values the interchange of learning objects standards. Nevertheless, for specialized domains these standards are insufficient to fully describe all the assets, especially when they are used as input for other eLearning services. To address this issue we extended an existing learning objects standard to the particular requirements of a specialized domain, namely the automatic evaluation of programming problems. The focus of this paper is the definition of programming problems as learning objects. We introduce a new schema to represent metadata related to automatic evaluation that cannot be conveniently represented using existing standards, such as: the type of automatic evaluation; the requirements of the evaluation engine; or the roles of different assets - tests cases, program solutions, etc. This new schema is being used in an interoperable repository of learning objects, called crimsonHex.

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Standards for learning objects focus primarily on content presentation. They were already extended to support automatic evaluation but it is limited to exercises with a predefined set of answers. The existing standards lack the metadata required by specialized evaluators to handle types of exercises with an indefinite set of solutions. To address this issue we extended existing learning object standards to the particular requirements of a specialized domain. We present a definition of programming problems as learning objects that is compatible both with Learning Management Systems and with systems performing automatic evaluation of programs. The proposed definition includes metadata that cannot be conveniently represented using existing standards, such as: the type of automatic evaluation; the requirements of the valuation engine; and the roles of different assets - tests cases, program solutions, etc. We present also the EduJudge project and its main services as a case study on the use of the proposed definition of programming problems as learning objects.

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This work is a contribution to the e-Framework, arguably the most prominent e-learning framework today, and consists of the definition of a service for the automatic evaluation of programming exercises. This evaluation domain differs from trivial evaluations modelled by languages such as the IMS Question & Test Interoperability (QTI) specification. Complex evaluation domains justify the development of specialized evaluators that participate in several business processes. These business processes can combine other type of systems such as Programming Contest Management Systems, Learning Management Systems, Integrated Development Environments and Learning Object Repositories where programming exercises are stored as Learning Objects. This contribution describes the implementation approaches used, more precisely, behaviours & requests, use & interactions, applicable standards, interface definition and usage scenarios.

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Vishnu is a tool for XSLT visual programming in Eclipse - a popular and extensible integrated development environment. Rather than writing the XSLT transformations, the programmer loads or edits two document instances, a source document and its corresponding target document, and pairs texts between then by drawing lines over the documents. This form of XSLT programming is intended for simple transformations between related document types, such as HTML formatting or conversion among similar formats. Complex XSLT programs involving, for instance, recursive templates or second order transformations are out of the scope of Vishnu. We present the architecture of Vishnu composed by a graphical editor and a programming engine. The editor is an Eclipse plug-in where the programmer loads and edits document examples and pairs their content using graphical primitives. The programming engine receives the data collected by the editor and produces an XSLT program. The design of the engine and the process of creation of an XSLT program from examples are also detailed. It starts with the generation of an initial transformation that maps source document to the target document. This transformation is fed to a rewrite process where each step produces a refined version of the transformation. Finally, the transformation is simplified before being presented to the programmer for further editing.

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The e-Framework is arguably the most prominent e-learning framework currently in use. For this reason it was selected as basis for modelling a programming exercises evaluation service. The purpose of this type of evaluator is to mark and grade exercises in computer programming courses and in programming contests. By exposing its functions as services a programming exercise evaluator is able to participate in business processes integrating different system types, such as Programming Contest Management Systems, Learning Management Systems, Integrated Development Environments and Learning Object Repositories. This paper formalizes the approaches to be used in the implementation of a programming exercise evaluator as a service on the e-Framework.

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It is widely accepted that solving programming exercises is fundamental to learn how to program. Nevertheless, solving exercises is only effective if students receive an assessment on their work. An exercise solved wrong will consolidate a false belief, and without feedback many students will not be able to overcome their difficulties. However, creating, managing and accessing a large number of exercises, covering all the points in the curricula of a programming course, in classes with large number of students, can be a daunting task without the appropriated tools working in unison. This involves a diversity of tools, from the environments where programs are coded, to automatic program evaluators providing feedback on the attempts of students, passing through the authoring, management and sequencing of programming exercises as learning objects. We believe that the integration of these tools will have a great impact in acquiring programming skills. Our research objective is to manage and coordinate a network of eLearning systems where students can solve computer programming exercises. Networks of this kind include systems such as learning management systems (LMS), evaluation engines (EE), learning objects repositories (LOR) and exercise resolution environments (ERE). Our strategy to achieve the interoperability among these tools is based on a shared definition of programming exercise as a Learning Object (LO).