870 resultados para Multicriteria Decision Support Systems
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Neste artigo se desenvolvem alternativas de abordagem multicritério visando à seleção de municípios para a implementação de políticas públicas de educação. Considerando que a situação da educação no Brasil apresenta grande variabilidade, o que impacta as demandas educacionais por políticas públicas de educação de forma diferente em diferentes regiões, verifica-se a necessidade de critérios objetivos para a seleção de pontos de aplicação de recursos para o combate a desigualdades nessa área. Em particular, se discute o emprego do Índice de Desenvolvimento Humano como fundamento para decisões na área educacional. Além disso, visa-se a estabelecer condições para a comparação dessas situações segundo diferentes critérios utilizados para fundamentar políticas públicas de educação.
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A adoção da modelagem institucional de governança do processo de avaliação ambiental norte-americano, centrada na figura da agência líder, deverá demandar a edição de uma lei formal, prevendo o referido arranjo jurídico-institucional, na forma de uma moldura (framework) adaptável às necessidades especificas e peculiaridades de cada setor da Administração. Dessa forma, a referida lei formal funcionaria como uma norma geral, e como tal poderia ser complementada pela legislação infralegal, que viria a estabelecer as disposições especificas para dar efetividade ao instituo da agência líder nos setores em que seja desejável e oportuna a implantação do mesmo, a critério da Administração. Destarte, a atuação do Poder Legislativo estaria restrita à introdução ao sistema jurídico doméstico do instituto estrangeiro, estabelecendo apenas seus contornos básicos, cabendo à Administração a avaliação da oportunidade e conveniência da escolha dos setores específicos, do estabelecimento dos contornos normativos e do momento da efetiva regulamentação concreta do instituto.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The main goal of this dissertation is to develop a Multi Criteria Decision Aid Model to be used in Oils and Gas perforation rigs contracts choices. The developed model should permit the utilization of multiples criterions, covering problems that exist with models that mainly use the price of the contracts as its decision criterion. The AHP has been chosen because its large utilization, not only academic, but in many other areas, its simplicity of use and flexibility, and also fill all the requirements necessary to complete the task. The development of the model was conducted by interviews and surveys with one specialist in this specific area, who also acts as the main actor on the decision process. The final model consists in six criterions: Costs, mobility, automation, technical support, how fast the service could be concluded and availability to start the operations. Three rigs were chosen as possible solutions for the problem. The results reached by the utilizations of the model suggests that the utilization of AHP as a decision support system in this kind of situation is possible, allowing a simplifications of the problem, and also it s a useful tool to improve every one involved on the process s knowledge about the problem subject, and its possible solutions
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This work presents a hybrid approach for the supplier selection problem in Supply Chain Management. We joined decision-making philosophy by researchers from business school and researchers from engineering in order to deal with the problem more extensively. We utilized traditional multicriteria decision-making methods, like AHP and TOPSIS, in order to evaluate alternatives according decision maker s preferences. The both techiniques were modeled by using definitions from the Fuzzy Sets Theory to deal with imprecise data. Additionally, we proposed a multiobjetive GRASP algorithm to perform an order allocation procedure between all pre-selected alternatives. These alternatives must to be pre-qualified on the basis of the AHP and TOPSIS methods before entering the LCR. Our allocation procedure has presented low CPU times for five pseudorandom instances, containing up to 1000 alternatives, as well as good values for all considered objectives. This way, we consider the proposed model as appropriate to solve the supplier selection problem in the SCM context. It can be used to help decision makers in reducing lead times, cost and risks in their supply chain. The proposed model can also improve firm s efficiency in relation to business strategies, according decision makers, even when a large number of alternatives must be considered, differently from classical models in purchasing literature
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Breast cancer, despite being one of the leading causes of death among women worldwide is a disease that can be cured if diagnosed early. One of the main techniques used in the detection of breast cancer is the Fine Needle Aspirate FNA (aspiration puncture by thin needle) which, depending on the clinical case, requires the analysis of several medical specialists for the diagnosis development. However, such diagnosis and second opinions have been hampered by geographical dispersion of physicians and/or the difficulty in reconciling time to undertake work together. Within this reality, this PhD thesis uses computational intelligence in medical decision-making support for remote diagnosis. For that purpose, it presents a fuzzy method to assist the diagnosis of breast cancer, able to process and sort data extracted from breast tissue obtained by FNA. This method is integrated into a virtual environment for collaborative remote diagnosis, whose model was developed providing for the incorporation of prerequisite Modules for Pre Diagnosis to support medical decision. On the fuzzy Method Development, the process of knowledge acquisition was carried out by extraction and analysis of numerical data in gold standard data base and by interviews and discussions with medical experts. The method has been tested and validated with real cases and, according to the sensitivity and specificity achieved (correct diagnosis of tumors, malignant and benign respectively), the results obtained were satisfactory, considering the opinions of doctors and the quality standards for diagnosis of breast cancer and comparing them with other studies involving breast cancer diagnosis by FNA.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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This paper investigates properties of integer programming models for a class of production planning problems. The models are developed within a decision support system to advise a sales team of the products on which to focus their efforts in gaining new orders in the short term. The products generally require processing on several manufacturing cells and involve precedence relationships. The cells are already (partially) committed with products for stock and to satisfy existing orders and therefore only the residual capacities of each cell in each time period of the planning horizon are considered. The determination of production recommendations to the sales team that make use of residual capacities is a nontrivial optimization problem. Solving such models is computationally demanding and techniques for speeding up solution times are highly desirable. An integer programming model is developed and various preprocessing techniques are investigated and evaluated. In addition, a number of cutting plane approaches have been applied. The performance of these approaches which are both general and application specific is examined.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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This paper is the result of real-scale physical modeling study designed to simulate the load-deformation characteristics of railroad foundation systems that include the railroad ties, the ballast, and the sub-base layers of a railroad embankment. The study presents comparisons of the application of dynamic loads of 100kN on the rails, and the resulting deformations during a 500,000 cycle testing period for three rail support systems; wood, concrete and steel. The results show that the deformation curve has an exponential shape, with the larger portion of the deformation occurring during the first 50,000 load cycles followed by a tendency to stabilize between 100,000 to 500,000 cycles. These results indicate that the critical phase of deformations of a new railroad is within the first 50,000 cycles of loading, and after that, it slowly attenuates as it approaches a stable value. The paper also presents empirically derived formulations for the estimation of the deformations of the rail supports as a result of rail traffic.
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This work combines symbolic machine learning and multiscale fractal techniques to generate models that characterize cellular rejection in myocardial biopsies and that can base a diagnosis support system. The models express the knowledge by the features threshold, fractal dimension, lacunarity, number of clusters, spatial percolation and percolation probability, all obtained with myocardial biopsies processing. Models were evaluated and the most significant was the one generated by the C4.5 algorithm for the features spatial percolation and number of clusters. The result is relevant and contributes to the specialized literature since it determines a standard diagnosis protocol. © 2013 Springer.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)