Repositório Colecção:
http://hdl.handle.net/10198/1248
2014-07-13T07:09:37ZAn hybrid approach for the parallelization of a block iterative algorithm
http://hdl.handle.net/10198/9848
Título: An hybrid approach for the parallelization of a block iterative algorithm
Autor: Balsa, Carlos; Guivarch, Ronan; Ruiz, Daniel; Zinadi, Mohamed
Resumo: The Cimmino method is a row projection method in which the original linear system is divided into subsystems. At every iteration, it computes one projection per subsystem and uses these projections to construct an approximation to the solution of the linear system. The usual parallelization strategy in block algorithms is to distribute the different blocks on the available processors. In this paper, we follow another approach where we do not perform explicitly this block distribution to processors within the code, but let the multi-frontal sparse solver MUMPS handle the data distribution and parallelism. The data coming from the subsystems defined by the block partition in the Block Cimmino method are gathered in an unique block diagonal sparse matrix which is analysed, distributed and factorized in parallel by MUMPS. Our target is to define a methodology for parallelism based only on the functionalities provided by general sparse solver libraries and how efficient this way of doing can be2011-01-01T00:00:00ZMultistart hooke and jeeves filter method for mixed variable optimization
http://hdl.handle.net/10198/9423
Título: Multistart hooke and jeeves filter method for mixed variable optimization
Autor: Fernandes, Florbela P.; Costa, M. Fernanda P.; Fernandes, Edite M.G.P.; Rocha, Ana Maria A. C.
Resumo: In this study, we propose an extended version of the Hooke and Jeeves algorithm that uses a simple heuristic to handle integer and/or binary variables and a filter set methodology to handle constraints. This proposal is integrated into a multistart method as a local solver and it is repeatedly called in order to compute different optimal solutions. Then, the best of all stored optimal solutions is selected as the global optimum. The performance of the new method is tested on benchmark problems. Its effectiveness is emphasized by a comparison with other well-known stochastic solvers.2013-01-01T00:00:00ZMathematical model of feet temperature
http://hdl.handle.net/10198/8317
Título: Mathematical model of feet temperature
Autor: Bento, David; Pereira, Ana I.; Monteiro, Fernando C.
Resumo: In this work it is consider the problem of finding the best approximation to characterize the feet temperature
distribution. For this study it was consider the nonlinear least squares technique, combined with penalty method, to identify
the function that approximate better the data obtained through thermographic images. The preliminary results indicate that the
best function approximation is based on trigonometric sums.2011-01-01T00:00:00ZPSSA : parallel stretched simulated annealing
http://hdl.handle.net/10198/8294
Título: PSSA : parallel stretched simulated annealing
Autor: Ribeiro, Tiago; Rufino, José; Pereira, Ana I.
Resumo: We consider the problem of finding all the global (and some local) minimizers of a given nonlinear optimization function (a class of problems also known as multi-local programming problems), using a novel approach based on Parallel Computing. The approach, named Parallel Stretched Simulated Annealing (PSSA), combines simulated annealing with stretching function technique, in a parallel execution environment. Our PSSA software allows to increase the resolution of the
search domains (thus facilitating the discovery of new solutions) while keeping the search time bounded. The software was
tested with a set of well known problems and some numerical results are presented.2011-01-01T00:00:00Z