Estudi comparatiu de l'algorisme basat en una colònia artificial d'abelles

La finalitat d'aquest projecte és la realització d'un estudi comparatiu de l'algoritme basat en una colònia artificial d'abelles, Artificial Bee Colony (ABC), comparat amb un conjunt d'algoritmes fonamentats en el paradigma de la computació evolutiva. S'utilitzarà l'eficàcia a l'hora d'optimitzar diverses funcions com a mesura comparativa. Els algoritmes amb els quals es comparara l'algoritme ABC són: algoritmes genètics, evolució diferencial i optimització amb eixam de partícules.

Swarm Intelligent Selection and Optimization of Machining System Parameters for Microchannel Fabrication in Medical Devices

Current technology trends in medical device industry calls for fabrication of massive arrays of microfeatures such as microchannels on to nonsilicon material substrates with high accuracy, superior precision, and high throughput. Microchannels are typical features used in medical devices for medication dosing into the human body, analyzing DNA arrays or cell cultures. In this study, the capabilities of machining systems for micro-end milling have been evaluated by conducting experiments, regression modeling, and response surface methodology. In machining experiments by using micromilling, arrays of microchannels are fabricated on aluminium and titanium plates, and the feature size and accuracy (width and depth) and surface roughness are measured. Multicriteria decision making for material and process parameters selection for desired accuracy is investigated by using particle swarm optimization (PSO) method, which is an evolutionary computation method inspired by genetic algorithms (GA). Appropriate regression models are utilized within the PSO and optimum selection of micromilling parameters; microchannel feature accuracy and surface roughness are performed. An analysis for optimal micromachining parameters in decision variable space is also conducted. This study demonstrates the advantages of evolutionary computing algorithms in micromilling decision making and process optimization investigations and can be expanded to other applications

A Model-to-model analysis of the repeated Prisoners' Dilemma: genetic algorithms vs. evolutionary dynamics

We study the properties of the well known Replicator Dynamics when applied to a finitely repeated version of the Prisoners' Dilemma game. We characterize the behavior of such dynamics under strongly simplifying assumptions (i.e. only 3 strategies are available) and show that the basin of attraction of defection shrinks as the number of repetitions increases. After discussing the difficulties involved in trying to relax the 'strongly simplifying assumptions' above, we approach the same model by means of simulations based on genetic algorithms. The resulting simulations describe a behavior of the system very close to the one predicted by the replicator dynamics without imposing any of the assumptions of the analytical model. Our main conclusion is that analytical and computational models are good complements for research in social sciences. Indeed, while on the one hand computational models are extremely useful to extend the scope of the analysis to complex scenar

Computation of an integral basis of a quartic number field

"Vegeu el resum a l'inici del document del fitxer adjunt."

Computation of an integral basis of quartic number field

"Vegeu el resum a l'inici del document del fitxer ajunt."

Fast numerical algorithms for the computation of invariant tori in Hamiltonian systems

In this paper, we develop numerical algorithms that use small requirements of storage and operations for the computation of invariant tori in Hamiltonian systems (exact symplectic maps and Hamiltonian vector fields). The algorithms are based on the parameterization method and follow closely the proof of the KAM theorem given in [LGJV05] and [FLS07]. They essentially consist in solving a functional equation satisfied by the invariant tori by using a Newton method. Using some geometric identities, it is possible to perform a Newton step using little storage and few operations. In this paper we focus on the numerical issues of the algorithms (speed, storage and stability) and we refer to the mentioned papers for the rigorous results. We show how to compute efficiently both maximal invariant tori and whiskered tori, together with the associated invariant stable and unstable manifolds of whiskered tori. Moreover, we present fast algorithms for the iteration of the quasi-periodic cocycles and the computation of the invariant bundles, which is a preliminary step for the computation of invariant whiskered tori. Since quasi-periodic cocycles appear in other contexts, this section may be of independent interest. The numerical methods presented here allow to compute in a unified way primary and secondary invariant KAM tori. Secondary tori are invariant tori which can be contracted to a periodic orbit. We present some preliminary results that ensure that the methods are indeed implementable and fast. We postpone to a future paper optimized implementations and results on the breakdown of invariant tori.

Omnidirectional Depth Computation from a Single Image

Omnidirectional cameras offer a much wider field of view than the perspective ones and alleviate the problems due to occlusions. However, both types of cameras suffer from the lack of depth perception. A practical method for obtaining depth in computer vision is to project a known structured light pattern on the scene avoiding the problems and costs involved by stereo vision. This paper is focused on the idea of combining omnidirectional vision and structured light with the aim to provide 3D information about the scene. The resulting sensor is formed by a single catadioptric camera and an omnidirectional light projector. It is also discussed how this sensor can be used in robot navigation applications

On optimal computation of MPLS label binding for multipoint-to-point connections

Most network operators have considered reducing Label Switched Routers (LSR) label spaces (i.e. the number of labels that can be used) as a means of simplifying management of underlaying Virtual Private Networks (VPNs) and, hence, reducing operational expenditure (OPEX). This letter discusses the problem of reducing the label spaces in Multiprotocol Label Switched (MPLS) networks using label merging - better known as MultiPoint-to-Point (MP2P) connections. Because of its origins in IP, MP2P connections have been considered to have tree- shapes with Label Switched Paths (LSP) as branches. Due to this fact, previous works by many authors affirm that the problem of minimizing the label space using MP2P in MPLS - the Merging Problem - cannot be solved optimally with a polynomial algorithm (NP-complete), since it involves a hard- decision problem. However, in this letter, the Merging Problem is analyzed, from the perspective of MPLS, and it is deduced that tree-shapes in MP2P connections are irrelevant. By overriding this tree-shape consideration, it is possible to perform label merging in polynomial time. Based on how MPLS signaling works, this letter proposes an algorithm to compute the minimum number of labels using label merging: the Full Label Merging algorithm. As conclusion, we reclassify the Merging Problem as Polynomial-solvable, instead of NP-complete. In addition, simulation experiments confirm that without the tree-branch selection problem, more labels can be reduced

Behavioural Flexibility: evolutionary past and its role in a changing world

A través de la historia de la vida, gran parte de los organismos han desarrollado estrategias para responder a un mundo en constante cambio. Hoy en día, las actividades humanas producen cambios ambientales a una velocidad sin precedentes, lo cual se traduce en grandes desafíos para la persistencia de biodiversidad. Esta investigación evalúa las respuesta de los animales a los cambios ambientales enfocándose en la flexibilidad del comportamiento como estrategia adaptativa. En una primera aproximación a una escala evolutiva, se otorgan evidencias del vínculo hasta ahora tenue entre la cognición e historias de vida, entregando un claro apoyo a la relación entre longevidad, vida reproductiva y el tamaño del cerebro en mamíferos. La longevidad es el centro de muchas hipótesis respecto a las ventajas de desarrollar un cerebro grande, como por ejemplo en la hipótesis del buffer cognitivo y las respuestas flexibles frente a nuevos ambientes. En un segundo nivel, se abordan factores extrínsecos e intrínsecos que podrían explicar las diferencias individuales en innovación, un componente clave en la flexibilidad del comportamiento. Por medio de una aproximación experimental, se evalúan potenciales escenarios que podrían conducir a consistentes diferencias individuales en uno de los principales factores subyacentes a la innovación (i.e. la motivación), y el potencial control endocrino sobre estos escenarios. Posteriormente, con el objetivo de evaluar la respuesta de los animales frente a los cambios ambientales actuales, se explora la respuesta de los animales frente a una de las actividades humanas mas disruptivas sobre los ecosistemas, la urbanización. Por medio de un analisis filogenetico comparativo a nivel global en aves se abordan los mecanismos implicados en la perdida de biodiversidad observada en ambientes urbanos. Los resultados entregan evidencias sobre la importancia de procesos de dispersión local junto con el papel clave de los rasgos de historia de vida, pero en un sentido diferente al clasicamente pensado. Finalmente por medio de una revisión bibliográfica se entregan evidencias teóricas y empíricas que respaldan el rol clave de la flexibilidad del comportamiento en confrontar los desafíos de una vida urbana. La integración de estos resultados muestra cómo el pasado evolutivo contribuye a hacer frente a los retos ambientales actuales, y pone de relieve posibles consecuencias ante un planeta más cambiante que nunca.

Transmission delays in residual computation

The design of control, estimation or diagnosis algorithms most often assumes that all available process variables represent the system state at the same instant of time. However, this is never true in current network systems, because of the unknown deterministic or stochastic transmission delays introduced by the communication network. During the diagnosing stage, this will often generate false alarms. Under nominal operation, the different transmission delays associated with the variables that appear in the computation form produce discrepancies of the residuals from zero. A technique aiming at the minimisation of the resulting false alarms rate, that is based on the explicit modelling of communication delays and on their best-case estimation is proposed

Behavioural Flexibility: evolutionary past and its role in a changing world

A través de la historia de la vida, gran parte de los organismos han desarrollado estrategias para responder a un mundo en constante cambio. Hoy en día, las actividades humanas producen cambios ambientales a una velocidad sin precedentes, lo cual se traduce en grandes desafíos para la persistencia de biodiversidad. Esta investigación evalúa las respuesta de los animales a los cambios ambientales enfocándose en la flexibilidad del comportamiento como estrategia adaptativa. En una primera aproximación a una escala evolutiva, se otorgan evidencias del vínculo hasta ahora tenue entre la cognición e historias de vida, entregando un claro apoyo a la relación entre longevidad, vida reproductiva y el tamaño del cerebro en mamíferos. La longevidad es el centro de muchas hipótesis respecto a las ventajas de desarrollar un cerebro grande, como por ejemplo en la hipótesis del buffer cognitivo y las respuestas flexibles frente a nuevos ambientes. En un segundo nivel, se abordan factores extrínsecos e intrínsecos que podrían explicar las diferencias individuales en innovación, un componente clave en la flexibilidad del comportamiento. Por medio de una aproximación experimental, se evalúan potenciales escenarios que podrían conducir a consistentes diferencias individuales en uno de los principales factores subyacentes a la innovación (i.e. la motivación), y el potencial control endocrino sobre estos escenarios. Posteriormente, con el objetivo de evaluar la respuesta de los animales frente a los cambios ambientales actuales, se explora la respuesta de los animales frente a una de las actividades humanas mas disruptivas sobre los ecosistemas, la urbanización. Por medio de un analisis filogenetico comparativo a nivel global en aves se abordan los mecanismos implicados en la perdida de biodiversidad observada en ambientes urbanos. Los resultados entregan evidencias sobre la importancia de procesos de dispersión local junto con el papel clave de los rasgos de historia de vida, pero en un sentido diferente al clasicamente pensado. Finalmente por medio de una revisión bibliográfica se entregan evidencias teóricas y empíricas que respaldan el rol clave de la flexibilidad del comportamiento en confrontar los desafíos de una vida urbana. La integración de estos resultados muestra cómo el pasado evolutivo contribuye a hacer frente a los retos ambientales actuales, y pone de relieve posibles consecuencias ante un planeta más cambiante que nunca.

A Monte Carlo method for accelerating the computation of animated radiosity sequences

Realistic rendering animation is known to be an expensive processing task when physically-based global illumination methods are used in order to improve illumination details. This paper presents an acceleration technique to compute animations in radiosity environments. The technique is based on an interpolated approach that exploits temporal coherence in radiosity. A fast global Monte Carlo pre-processing step is introduced to the whole computation of the animated sequence to select important frames. These are fully computed and used as a base for the interpolation of all the sequence. The approach is completely view-independent. Once the illumination is computed, it can be visualized by any animated camera. Results present significant high speed-ups showing that the technique could be an interesting alternative to deterministic methods for computing non-interactive radiosity animations for moderately complex scenarios

An Analysis of black-box optimization problems in reinsurance: evolutionary-based approaches

Black-box optimization problems (BBOP) are de ned as those optimization problems in which the objective function does not have an algebraic expression, but it is the output of a system (usually a computer program). This paper is focussed on BBOPs that arise in the eld of insurance, and more speci cally in reinsurance problems. In this area, the complexity of the models and assumptions considered to de ne the reinsurance rules and conditions produces hard black-box optimization problems, that must be solved in order to obtain the optimal output of the reinsurance. The application of traditional optimization approaches is not possible in BBOP, so new computational paradigms must be applied to solve these problems. In this paper we show the performance of two evolutionary-based techniques (Evolutionary Programming and Particle Swarm Optimization). We provide an analysis in three BBOP in reinsurance, where the evolutionary-based approaches exhibit an excellent behaviour, nding the optimal solution within a fraction of the computational cost used by inspection or enumeration methods.