10 resultados para many-objective problems

em Universidade do Minho


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Projeto de Investigação integrado de mestrado Internacional em Sustentabilidade do Ambiente Construído

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Relatório de estágio de mestrado em Geografia (área de especialização em Planeamento e Gestão do Território)

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BACKGROUND: Machinery safety issues are a challenge facing manufacturers who are supposed to create and provide products in a better and faster way. In spite of their construction and technological advance, they still contribute to many potential hazards for operators and those nearby. OBJECTIVE: The aim of this study is to investigate safety aspects of metal machinery offered for sale on Internet market according to compliance with minimum and fundamental requirements. METHODS: The study was carried out with the application of a checklist prepared on the basis of Directive 2006/42/EC and Directive 2009/104/EC and regulations enforcing them into Polish law. RESULTS: On the basis of the study it was possible to reveal the safety aspects that were not met in practice. It appeared that in the case of minimum requirements the most relevant problems concerned information, signal and control elements, technology and machinery operations, whereas as far as fundamental aspects are concerned it was hard to assure safe work process. CONCLUSIONS: In spite of the fact that more and more legal acts binding in the Member Countries of the European Union are being introduced to alleviate the phenomenon, these regulations are often not fulfilled.

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Dissertação de Mestrado em Engenharia Informática

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Tese de Doutoramento em Ciências da Educação (Área de Conhecimento: Educação ambiental e para a Sustentabilidade)

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The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.

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In this paper, we propose an extension of the firefly algorithm (FA) to multi-objective optimization. FA is a swarm intelligence optimization algorithm inspired by the flashing behavior of fireflies at night that is capable of computing global solutions to continuous optimization problems. Our proposal relies on a fitness assignment scheme that gives lower fitness values to the positions of fireflies that correspond to non-dominated points with smaller aggregation of objective function distances to the minimum values. Furthermore, FA randomness is based on the spread metric to reduce the gaps between consecutive non-dominated solutions. The obtained results from the preliminary computational experiments show that our proposal gives a dense and well distributed approximated Pareto front with a large number of points.

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Dissertação de mestrado em Engenharia Industrial (área de especialização em Gestão Industrial)

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Dissertação de mestrado integrado em Engenharia Civil

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Tese de Doutoramento em Psicologia Aplicada.