8 resultados para local sequence alignment problem
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Trabalho apresentado no âmbito do European Master in Computational Logics, como requisito parcial para obtenção do grau de Mestre em Computational Logics
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J Biol Inorg Chem (2011) 16:1241–1254 DOI 10.1007/s00775-011-0812-9
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Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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Thesis submitted in fulfilment of the requirements for the Degree of Master of Science in Computer Science
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Optimization is a very important field for getting the best possible value for the optimization function. Continuous optimization is optimization over real intervals. There are many global and local search techniques. Global search techniques try to get the global optima of the optimization problem. However, local search techniques are used more since they try to find a local minimal solution within an area of the search space. In Continuous Constraint Satisfaction Problems (CCSP)s, constraints are viewed as relations between variables, and the computations are supported by interval analysis. The continuous constraint programming framework provides branch-and-prune algorithms for covering sets of solutions for the constraints with sets of interval boxes which are the Cartesian product of intervals. These algorithms begin with an initial crude cover of the feasible space (the Cartesian product of the initial variable domains) which is recursively refined by interleaving pruning and branching steps until a stopping criterion is satisfied. In this work, we try to find a convenient way to use the advantages in CCSP branchand- prune with local search of global optimization applied locally over each pruned branch of the CCSP. We apply local search techniques of continuous optimization over the pruned boxes outputted by the CCSP techniques. We mainly use steepest descent technique with different characteristics such as penalty calculation and step length. We implement two main different local search algorithms. We use “Procure”, which is a constraint reasoning and global optimization framework, to implement our techniques, then we produce and introduce our results over a set of benchmarks.
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Combinatorial Optimization Problems occur in a wide variety of contexts and generally are NP-hard problems. At a corporate level solving this problems is of great importance since they contribute to the optimization of operational costs. In this thesis we propose to solve the Public Transport Bus Assignment problem considering an heterogeneous fleet and line exchanges, a variant of the Multi-Depot Vehicle Scheduling Problem in which additional constraints are enforced to model a real life scenario. The number of constraints involved and the large number of variables makes impracticable solving to optimality using complete search techniques. Therefore, we explore metaheuristics, that sacrifice optimality to produce solutions in feasible time. More concretely, we focus on the development of algorithms based on a sophisticated metaheuristic, Ant-Colony Optimization (ACO), which is based on a stochastic learning mechanism. For complex problems with a considerable number of constraints, sophisticated metaheuristics may fail to produce quality solutions in a reasonable amount of time. Thus, we developed parallel shared-memory (SM) synchronous ACO algorithms, however, synchronism originates the straggler problem. Therefore, we proposed three SM asynchronous algorithms that break the original algorithm semantics and differ on the degree of concurrency allowed while manipulating the learned information. Our results show that our sequential ACO algorithms produced better solutions than a Restarts metaheuristic, the ACO algorithms were able to learn and better solutions were achieved by increasing the amount of cooperation (number of search agents). Regarding parallel algorithms, our asynchronous ACO algorithms outperformed synchronous ones in terms of speedup and solution quality, achieving speedups of 17.6x. The cooperation scheme imposed by asynchronism also achieved a better learning rate than the original one.
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The emergence of new technologies has introduced significant changes in the citizens life’s. There is a constant evolution of technological means and profound impact of their use in the habits of life of the human being. These new technological media are important tools in labor relations. The working and businesses worlds are increasingly turning to these new technologies, so that the use of video surveillance in the workplace is nowadays common. New technologies in general and the use of video surveillance in workplace in particular are providing ways to allow control of the work performance that are desired by most employers. However, the collection of images in the workplace often collides with the fundamental rights and freedoms of workers, in particular, with the right to privacy. The subject concerns the question of investigating is whether the images collected in workplace can be used as evidence in disciplinary proceedings. In fact, this issue is controversial. Doctrine and jurisprudence defend, at least, two responses for the same question. Those who understand that the evidence may be admitted for not violate any right of the worker, and others who argue that the evidence should not be admitted in disciplinary office. In the Portuguese legal system, there is, even, a new intermediate theory that begins to be defended, that only on certain occasions the evidence may be admitted. The solution to this problem involves the study of employment law and data video surveillance processing. Analysis of workers fundamental rights is fundamental to come to a grounded conclusion.