5 resultados para feature-based design

em Universidad de Alicante


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En este artículo se investigan técnicas automáticas para encontrar un modelo óptimo de características en el caso de un analizador de dependencias basado en transiciones. Mostramos un estudio comparativo entre algoritmos de búsqueda, sistemas de validación y reglas de decisión demostrando al mismo tiempo que usando nuestros métodos es posible conseguir modelos complejos que proporcionan mejores resultados que los modelos que siguen configuraciones por defecto.

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In this work, we present a systematic method for the optimal development of bioprocesses that relies on the combined use of simulation packages and optimization tools. One of the main advantages of our method is that it allows for the simultaneous optimization of all the individual components of a bioprocess, including the main upstream and downstream units. The design task is mathematically formulated as a mixed-integer dynamic optimization (MIDO) problem, which is solved by a decomposition method that iterates between primal and master sub-problems. The primal dynamic optimization problem optimizes the operating conditions, bioreactor kinetics and equipment sizes, whereas the master levels entails the solution of a tailored mixed-integer linear programming (MILP) model that decides on the values of the integer variables (i.e., number of equipments in parallel and topological decisions). The dynamic optimization primal sub-problems are solved via a sequential approach that integrates the process simulator SuperPro Designer® with an external NLP solver implemented in Matlab®. The capabilities of the proposed methodology are illustrated through its application to a typical fermentation process and to the production of the amino acid L-lysine.

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We address the optimization of discrete-continuous dynamic optimization problems using a disjunctive multistage modeling framework, with implicit discontinuities, which increases the problem complexity since the number of continuous phases and discrete events is not known a-priori. After setting a fixed alternative sequence of modes, we convert the infinite-dimensional continuous mixed-logic dynamic (MLDO) problem into a finite dimensional discretized GDP problem by orthogonal collocation on finite elements. We use the Logic-based Outer Approximation algorithm to fully exploit the structure of the GDP representation of the problem. This modelling framework is illustrated with an optimization problem with implicit discontinuities (diver problem).

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The economic design of a distillation column or distillation sequences is a challenging problem that has been addressed by superstructure approaches. However, these methods have not been widely used because they lead to mixed-integer nonlinear programs that are hard to solve, and require complex initialization procedures. In this article, we propose to address this challenging problem by substituting the distillation columns by Kriging-based surrogate models generated via state of the art distillation models. We study different columns with increasing difficulty, and show that it is possible to get accurate Kriging-based surrogate models. The optimization strategy ensures that convergence to a local optimum is guaranteed for numerical noise-free models. For distillation columns (slightly noisy systems), Karush–Kuhn–Tucker optimality conditions cannot be tested directly on the actual model, but still we can guarantee a local minimum in a trust region of the surrogate model that contains the actual local minimum.

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Nowadays, on a global level, the Higher Education System has a complex and broad horizon of curricular tools to use in the teaching and learning process. In addition to these new educational instruments, full of possibilities, we face specific socio-economic conditions that affect in a significantly way the Curriculum Development in certain knowledge areas (areas traditionally built on a methodology based on a physical presence of students in the classroom). Some areas such as Restoration, Rehabilitation or Construction Pathologies, and the construction sector in general, require very defined and particular knowledge that only a small number of experts claim as specialized training. All these aspects condition the teaching methodology performed in a physical classroom at a university campus (the only option used until recent years) and made us consider the integration of online teaching in these areas too. The present work shows the teaching methodology used for the development of two online courses, where we offer distance learning for "highly specialized" formation in the Edification area (an area where traditionally there was only classroom training). At the beginning, both courses were designed by classroom training, but got a really small number of applications due to the specialized topic proposed. Later, we proposed a "Curriculum Redesign" of the contents, offering an online modality, which implied a significant demand both within and outside the university area. A notable feature of this educational experience is the great spectrum opened for attendees of both courses in the online version. This situation improved significantly the "Curriculum Development" for the student and implied an interesting new proposal on the offered contents and materials (what would have been really difficult to get in a face to face classroom). In conclusion, the absence of certain types of specialized contents in the academic university curricula makes essential to raise new methodologies to save the gap in this area through additional training courses as those analyzed in this paper. Thus, our experience opens a debate on the appropriateness of implementing online training in relation to the face to face training in constructive content subjects and, especially, presents a new scheme, not without controversy, for the curriculum design.