An optimization of the thermal behavior of a high-power salient-pole electrical machine is presented. Temperatures are calculated with the lumped method, which provides the thermal trends with relatively low computati...
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An optimization of the thermal behavior of a high-power salient-pole electrical machine is presented. Temperatures are calculated with the lumped method, which provides the thermal trends with relatively low computational cost. This model is used to define an aggregated objective function of our nonlinear thermal optimization problem by combining the mean solid temperature with the maximum temperature criteria. The 13 design variables correspond to the main volumetric flow rates in the electrical machine, which are bounded and subjected to a nonlinear constraint, assuming a fixed geometry. Two MATLAB optimization algorithms were tested: the active-set (FMINCON solver) and the genetic algorithm (GA). Due to the strong nonlinearities of the model and the resulting nonconvex optimization problem, the GA is likely to give better results. Minimizing the mean solid temperature was demonstrated to be more important than the maximum temperature criterion. A strategic flow configuration is found to send fresh air to the second half of the cooling circuit, where air usually arrives heated. This optimal configuration provides better cooling than its current modeled configuration. This methodology should be of interest during the development phase.
Nonnegative matrix factorization (NMF) has been successfully used as a clustering method especially for flat partitioning of documents. In this paper, we propose an efficient hierarchical document clustering method ba...
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ISBN:
(纸本)9781450321747
Nonnegative matrix factorization (NMF) has been successfully used as a clustering method especially for flat partitioning of documents. In this paper, we propose an efficient hierarchical document clustering method based on a new algorithm for rank-2 NMF. When the two block coordinate descent framework of nonnegative least squares is applied to computing rank-2 NMF, each subproblem requires a solution for nonnegative least squares with only two columns in the matrix. We design the algorithm for rank-2 NMF by exploiting the fact that an exhaustive search for the optimal activeset can be performed extremely fast when solving these NNLS problems. In addition, we design a measure based on the results of rank-2 NMF for determining which leaf node should be further split. On a number of text data sets, our proposed method produces high-quality tree structures in significantly less time compared to other methods such as hierarchical K-means, standard NMF, and latent Dirichlet allocation.
We present the thermal optimization study of a single inlet 90 T-junction. Head losses in association with the lumped method are used to calculate the 2D temperature field from a specific geometrical configuration, he...
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We present the thermal optimization study of a single inlet 90 T-junction. Head losses in association with the lumped method are used to calculate the 2D temperature field from a specific geometrical configuration, heat sources, boundary conditions and available ventilation power. This simple case is used as a benchmark to show a possible optimization methodology and to test 4 optimization algorithms suitable to non-linear problems;they are the active-set, Interior Point, Genetic algorithm and Particle Swarm Optimization. The optimization problem is defined by an Aggregated Objective Function (AOF) that depends on three geometrical parameters which are subjected to linear and non-linear constraints. In order to consider not only the global thermal behavior, but also local hotspots, the AOF combines mean solid temperature pondered by its volume and the maximal temperature. Five weights for these criteria were tested. The physical interpretation of different points helped to identify the optimal geometrical characteristics. All optimization algorithms demonstrated to be able to avoid local minima with this benchmark, if properly used. (C) 2011 Elsevier Masson SAS. All rights reserved.
In this paper, an algorithm for solving a mathematical programming problem with complementarity (or equilibrium) constraints (MPEC) is introduced, which uses the active-set methodology while maintaining the complement...
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In this paper, an algorithm for solving a mathematical programming problem with complementarity (or equilibrium) constraints (MPEC) is introduced, which uses the active-set methodology while maintaining the complementarity restrictions throughout the procedure. Finite convergence of the algorithm to a strongly stationary point of the MPEC is established under reasonable hypotheses. The algorithm can be easily implemented by adopting any active-set code for nonlinear programming. Computational experience is included to highlight the efficacy of the proposed method in practice.
Interface crack problems arising in quasibrittle fracture due to contact with cohesion or plasticity between the crack faces are considered. These problems are described by a hemivariational inequality. Its solvabilit...
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Interface crack problems arising in quasibrittle fracture due to contact with cohesion or plasticity between the crack faces are considered. These problems are described by a hemivariational inequality. Its solvability is guaranteed by the variational principle, which yields minimization of a nonconvex and nondifferentiable objective functional associated to the total potential energy. To compute solutions of the hemivariational inequality, a primal-dual active-set algorithm is suggested, which obeys global and monotone convergence properties. A numerical example of the quasibrittle fracture is presented.
This contribution describes an active-set algorithm for the optimization of regression support vector machines (SVMs). Its intended use is mainly system identification. Currently, SVMs are computed solving a QP proble...
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This contribution describes an active-set algorithm for the optimization of regression support vector machines (SVMs). Its intended use is mainly system identification. Currently, SVMs are computed solving a QP problem by working-setalgorithms like the SMO method. Although showing good results in general, they may perform weakly in some situations, particularly when solving regression problems. In these cases, active-set techniques (which are robust general-purpose QP solvers) have been shown to be a reasonable alternative. The paper considers how to adapt them to SVM regession with fixed or variable bias term and applies them to the identification of a condensing boiler.
In this paper a branch-and-bound algorithm is proposed for finding a global minimum to a Mathematical Programming Problem with Complementarity (or Equilibrium) Constraints (MPECs), which incorporates disjunctive cuts ...
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In this paper a branch-and-bound algorithm is proposed for finding a global minimum to a Mathematical Programming Problem with Complementarity (or Equilibrium) Constraints (MPECs), which incorporates disjunctive cuts for computing lower bounds and employs a Complementarity active-set algorithm for computing upper bounds. Computational results for solving MPECs associated with Bilivel Problems, NP-hard Linear Complementarity Problems, and Hinge Fitting Problems are presented to highlight the efficacy of the procedure in determining a global minimum for different classes of MPECs.
Consider a network in which a commodity flows at a variable rate across the arcs in order to meet supply/demand at the nodes, The aim is to optimally control the rate of flow such that a convex objective functional is...
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Consider a network in which a commodity flows at a variable rate across the arcs in order to meet supply/demand at the nodes, The aim is to optimally control the rate of flow such that a convex objective functional is minimized. This is an optimal control problem with a large number of states, and with an even larger number of controls. It is also complicated by storage bounds at the nodes leading to two state constraints for each node, We show, under some mild assumptions on the problem's parameters, that an exact solution to this state-constrained optimal control problem can be found efficiently without a complete discretization of the time variable, and develop a solution algorithm, based on the active-set-on-a-graph (ASG) algorithm for static convex flow problems. A brief description of a possible application as well as some numerical results are provided to illustrate the usefulness of the algorithm. Copyright (C) 2000 John Wiley & Sons, Ltd.
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