Solving multilocal optimization problems with a recursive parallel search of the feasible region

Stretched Simulated Annealing (SSA) combines simulated annealing with a stretching function technique, in order to solve multilocal programming problems. This work explores an approach to the parallelization of SSA, named PSSA-HeD, based on a recursive heterogeneous decomposition of the feasible region and the dynamic distribution of the resulting subdomains by the processors involved. Three PSSAHeD variants were implemented and evaluated, with distinct limits on the recursive search depth, offering different levels of numerical and computational efficiency. Numerical results are presented and discussed.This work was been supported by FCT (Fundação para a Ciência e Tecnologia) in the scope of the project PEst-OE/EEI/UI0319/2014

Solving constrained multilocal optimization problems with parallel stretched simulated annealing

Constrained multilocal programming optimization problems may be solved by solving a sequence of unconstrained problems. In turn, those unconstrained problems may be solved using techniques like the Stretched Simulated Annealing (SSA) method. In order to increase the solving performance and make possible the discovery of new optima, parallel approaches to SSA have been devised, like Parallel Stretched Simulated Annealing (PSSA). Recently, Constrained PSSA (coPSSA) was also proposed, coupling the penalty method with PSSA, in order to solve constrained problems. In this work, coPSSA is explored to solve four test problems using the l 1 penalty function. The effect of the variation of the reduction factor parameter of the l 1 penalty function is also studied.This work was been supported by FCT (Fundação para a Ciência e Tecnologia) in the scope of the project UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

coPSSA - constrained parallel stretched simulated annealing

Parallel Stretched Simulated Annealing (PSSA) solves unconstrained multilocal programming optimization problems in distributed memory clusters, by applying the Stretched Simulated Annealing optimization method, in parallel, to multiple sub-domains of the original feasible region. This work presents coPSSA (constrained Parallel Stretched Simulated Annealing), an hybrid application that combines shared memory based parallelism with PSSA, in order to efficiently solve constrained multilocal programming problems. We devise and evaluate two different parallel strategies for the search of solutions to these problems. Evaluation results from a small set of test problems often reach superlinear speedup in the solution search time, thus proving the merit of the coPSSA parallelization approach

Livro de atas do XVI Congresso da Associação Portuguesa de Investigação Operacional

Fundação para a Ciência e Tecnologia - FC

Efficient Learning Machines

Computer scienc

Parameter estimation using a genetic algorithm for complex catchment modelling systems.

Implementation of physically distributed catchment modelling systems reshapes the fundamental philosophy of traditional calibration approaches by supporting the concept of equifinality. Arising from the concept of equifinality, alternative behavioural parameter sets within a given catchment modelling system structure can generate similar levels of simulation performance. This concept is motivated by the existence of a variety of uncertainties associated with a complex catchment modelling system, such as an imperfect model structure, measurement errors in both the input data and the recorded flows, and unknown, or poorly defined, interactions among parameters. However, the difficulty of searching for behavioural parameter sets increases as the complexity of the catchment modelling systems increases. This study undertook an investigation on the feasibility and robustness of a real-value coding genetic algorithm (GA) for calibrating the physically distributed Storm Water Management Model (SWMM) using the Centennial Park catchment in Sydney as a case study. It was found that a real-value coding GA was a robust technique suitable to search for behavioural parameter sets and, in particular, it was found that this approach was capable of identifying the promising range of values for spatially variable parameters. Moreover, the widespread use of physically distributed catchment modelling systems has highlighted the importance of estimating the uncertainty in the parameter values and in the predictions obtained from a complex catchment modelling system as well as in catchment averaged, or lumped, systems that have been the focus of many previous studies. Bayesian inference has been shown to be a tool suitable for parameter uncertainty estimation in catchment modelling. However, the application of Bayesian inference faces difficulties in complex high-dimensional systems where there is little if any a priori knowledge about the proposal distribution of the parameters. In this study, a real-value coding GA was used to undertake uncertainty estimation on spatially variable control parameters with little a priori knowledge about the proposal distribution of parameters. After 50,000 evaluations, the marginal posterior distributions of spatially variable parameters which are associated with behavioural parameter sets were identified. The performance of a behavioural parameter set under a range of hydrological conditions was evaluated. Updating of the marginal distributions of these control parameters was implemented by adding additional calibration data. Interactions among the spatially variable control parameters were investigated also. Results based on the Pearson Correlation method indicate no clear relationship between any two control parameters. However, a methodology to detect relationships among groups of parameters was developed. Application of this methodology suggests that the simulation performance of SWMM was influenced by combinations of parameter values rather than values of the individual parameters. Finally, the predictive uncertainty associated with the existence of behavioural parameter sets was considered. A number of alternative strategies were used to evaluate the predictive performance. Consideration of the results suggests that use of a small number of parameter sets randomly selected from the large number of behavioural parameter sets was the best strategy in terms of efficiently obtaining predictive performance

Generalized averaged Gaussian quadrature and applications

A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal

MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described

Biometrics

Biometrics uses methods for unique recognition of humans based upon one or more intrinsic physical or behavioral traits. In computer science, particularly, biometrics is used as a form of identity access management and access control. It is also used to identify individuals in groups that are under surveillance. The book consists of 13 chapters, each focusing on a certain aspect of the problem. The book chapters are divided into three sections: physical biometrics, behavioral biometrics and medical biometrics. The key objective of the book is to provide comprehensive reference and text on human authentication and people identity verification from both physiological, behavioural and other points of view. It aims to publish new insights into current innovations in computer systems and technology for biometrics development and its applications. The book was reviewed by the editor Dr. Jucheng Yang, and many of the guest editors, such as Dr. Girija Chetty, Dr. Norman Poh, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park, Dr. Sook Yoon and so on, who also made a significant contribution to the book