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Comellas E.,Polytechnic University of Catalonia | Valdez S.I.,Center For Research In Mathematics Cimat Ac | Oller S.,Polytechnic University of Catalonia | Botello S.,Center For Research In Mathematics Cimat Ac
Composite Structures | Year: 2015

An optimization method to identify the material parameters of composite structures using an inverse method is proposed. This methodology compares experimental results with their numerical reproduction using the finite element method in order to obtain an estimation of the error between the results. This error estimation is then used by an evolutionary optimizer to determine, in an iterative process, the value of the material parameters which result in the best numerical fit. The novelty of the method is in the coupling between the simple genetic algorithm and the mixing theory used to numerically reproduce the composite behavior. The methodology proposed has been validated through a simple example which illustrates the exploitability of the method in relation to the modeling of damaged composite structures. © 2014 Elsevier Ltd. Source

Valdez S.I.,Center For Research In Mathematics Cimat Ac | Hernandez A.,Center For Research In Mathematics Cimat Ac | Botello S.,Center For Research In Mathematics Cimat Ac
Information Sciences | Year: 2013

This paper introduces a new approach for estimation of distribution algorithms called the Boltzmann Univariate Marginal Distribution Algorithm (BUMDA). It uses a Normal-Gaussian model to approximate the Boltzmann distribution, hence, formulae for computing the mean and variance parameters of the Gaussian model are derived from the analytical minimization of the Kullback-Leibler divergence. The resulting formulae explicitly introduces information about the fitness landscape for the Gaussian parameters computation, in consequence, the Gaussian distribution obtains a better bias to sample intensively the most promising regions than simply using the maximum likelihood estimator of the selected set. In addition, the BUMDA formulae needs only one user parameter. Accordingly to the experimental results, the BUMDA excels in its niche of application. We provide theoretical, graphical and statistical analysis to show the BUMDA performance contrasted with state of the art EDAs. © 2013 Elsevier Inc. All rights reserved. Source

Pesantes M.,Center For Research In Mathematics Cimat Ac | Lemus C.,Center For Research In Mathematics Cimat Ac | Mitre H.A.,Center For Research In Mathematics Cimat Ac | Mejia J.,Center For Research In Mathematics Cimat Ac
Proceedings - 2012 9th Electronics, Robotics and Automotive Mechanics Conference, CERMA 2012 | Year: 2012

Software Process Architecture is an emergent area of research, with little understanding, scarce experience and confusing terminology. Thus, technical concerns along with its evolution are difficult to express. And it has been until recent time that has received increasing attention as an important sub-area of Software Process Engineering. This paper aims to briefly present main topics of software process architecture addressing three main issues: What is a software process architecture?, How it is created? And who is responsible for building it? (i.e. definition, process and role). It also identifies some challenges and research directions by delineating a roadmap to facilitate its understanding and growth. © 2012 IEEE. Source

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