Optimization method for the determination of material parameters in damaged composite structures

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.Peer ReviewedPostprint (author’s final draft

Evolutionary computation for wind farm layout optimization

This paper presents the results of the second edition of the Wind Farm Layout Optimization Competition, which was held at the 22nd Genetic and Evolutionary Computation COnference (GECCO) in 2015. During this competition, competitors were tasked with optimizing the layouts of five generated wind farms based on a simplified cost of energy evaluation function of the wind farm layouts. Online and offline APIs were implemented in C++, Java, Matlab and Python for this competition to offer a common framework for the competitors. The top four approaches out of eight participating teams are presented in this paper and their results are compared. All of the competitors' algorithms use evolutionary computation, the research field of the conference at which the competition was held. Competitors were able to downscale the optimization problem size (number of parameters) by casting the wind farm layout problem as a geometric optimization problem. This strongly reduces the number of evaluations (limited in the scope of this competition) with extremely promising results

Optimización multiobjetivo de estructuras, utilizando algoritmos de estimación de distribución e información de vecindades

En este trabajo se presentan un conjunto de técnicas para la optimización multiobjetivo de estructuras (diseño óptimo automatizado), basadas en algoritmos de estimación de distribución. Esta nueva propuesta de solución utiliza el criterio de dominancia de Pareto para el manejo de las restricciones y los objetivos. Los objetivos a optimizar son: el peso mínimo de la estructura y el desplazamiento en nodos especificados. Las restricciones de diseño de las estructuras son: a) no exceder un esfuerzo Von Misses máximo, b) no presentar elementos desconectados por los lados y c) no presentar agujeros pequeños (del tamaño de un elemento). El algoritmo propuesto, utiliza información de las vecindades para mejorar la exploración hacia las soluciones más probables, y evitar mínimos locales. Se utiliza el método del elemento finito para evaluar las funciones objetivo y restricción(desplazamiento y esfuerzo)