Efficient list-generation techniques for scheduling assessment centers

Human resources managers often conduct assessment centers to evaluate candidates for a job position. During an assessment center, the candidates perform a series of tasks. The tasks require one or two assessors (e.g., managers or psychologists) that observe and evaluate the candidates. If an exercise is designed as a role-play, an actor is required who plays, e.g., an unhappy customer with whom the candidate has to deal with. Besides performing the tasks, each candidate has a lunch break within a prescribed time window. Each candidate should be observed by approximately half the number of the assessors; however, an assessor may not observe a candidate if they personally know each other. The planning problem consists of determining (1) resource-feasible start times of all tasks and lunch breaks and (2) a feasible assignment of assessors to candidates, such that the assessment center duration is minimized. We present a list-scheduling heuristic that generates feasible schedules for such assessment centers. We propose several novel techniques to generate the respective task lists. Our computational results indicate that our approach is capable of devising optimal or near-optimal schedules for real-world instances within short CPU time.

Grammar-Guided Evolutionary Construction of Bayesian networks

This paper proposes the EvoBANE system. EvoBANE automatically generates Bayesian networks for solving special-purpose problems. EvoBANE evolves a population of individuals that codify Bayesian networks until it finds near optimal individual that solves a given classification problem. EvoBANE has the flexibility to modify the constraints that condition the solution search space, self-adapting to the specifications of the problem to be solved. The system extends the GGEAS architecture. GGEAS is a general-purpose grammar-guided evolutionary automatic system, whose modular structure favors its application to the automatic construction of intelligent systems. EvoBANE has been applied to two classification benchmark datasets belonging to different application domains, and statistically compared with a genetic algorithm performing the same tasks. Results show that the proposed system performed better, as it manages different complexity constraints in order to find the simplest solution that best solves every problem.

Estrategias para el control microclimático del espacio entre edificaciones en clima cálido – húmedo

La presente investigación parte del problema en las zonas de clima cálido - húmedo en las cuales se producen impactos asociados a la incomodidad térmica producto de la intensa radiación solar, altas temperaturas y elevada humedad. Estos factores reducen la calidad de los espacios abiertos y desarrollan en la población una actitud de rechazo hacia el uso del microespacio urbano entre edificaciones en los desarrollos urbanos - conjuntos urbanos - , los mismos frecuentemente admiten soluciones que al parecer no contribuyen a la realización de las actividades comunes de esparcimiento de la población residente. Por lo tanto, el objetivo de la investigación es profundizar en la temática urbano - ambiental - social y el diseño urbano vinculada a la particularidad morfológica local, las condiciones microclimáticas, el uso del microespacio y los requerimientos de los usuarios. La finalidad de desarrollar estrategias de control microclimático del microespacio entre edificios en clima cálido - húmedo en búsqueda de soluciones óptimas que satisfagan las necesidades de los usuarios de los espacios exteriores en estas áreas residenciales. La investigación se centra en el estudio de las particularidades contextuales relacionadas con el microclima y las características urbanas - morfotipológicas, básicamente los factores microclimáticos (soleamiento y ventilación), los morfológicos y edificatorios y las características de las superficies (pavimentos). En coherencia con el objetivo propuesto el trabajo se desarrolla en cuatro fases: la primera aborda la revisión documental, literatura relevante e investigaciones relativas a la calidad ambiental, medio social, medio físico, el microespacio urbano, control y diseño sostenible, modelización proyectual y estrategias sostenibles; la segunda fase se refiere al marco contextual, características urbanas, datos climáticos locales, planes y procesos urbanos, tipologías y conformación urbana. En esta fase se describe el proceso de selección, análisis y evaluación urbano - ambiental de los casos de estudio (conjuntos residenciales). En la tercera fase se aborda el marco evaluativo y estudio de casos, consideraciones físicas, climáticas y valoración térmico - ambiental de los conjuntos residenciales seleccionados. En esta fase se aplican Técnicas Estadísticas y de Simulación Computacional y se analizan los resultados obtenidos. Finalmente, la cuarta fase propositiva incluye el establecimiento de Estrategias, Principios y Lineamientos de optimación térmica y se exponen las Conclusiones parciales de la tesis, alcances y perspectivas futuras. Finalmente, los resultados obtenidos en la investigación demuestran que el análisis en las experiencias de la realidad permiten comprobar que las situaciones y alteraciones ambientales sustanciales, los niveles de afectación térmica y las condiciones de confortabilidad e impacto derivan de las características urbanas, los componentes del microespacio y de las condiciones climáticas las cuales afectan el desarrollo de las actividades y el uso efectivo del microespacio entre edificios. El análisis de los factores morfo - climáticos incidentes y el estudio de los efectos de interacción contribuyen al establecimiento de Principios y Lineamientos para la evaluación y diseño sostenible del microespacio entre edificios y el uso correcto de los elementos del clima en estas áreas urbanas destinadas a la actividad social y al esparcimiento de la población residente. ABSTRACT This research starts from the problem of hot - humid climate zones where impacts related to thermal discomfort are produced as a result from the intense solar radiation and high temperatures and humidity. These factors reduce the quality of open spaces and people develop an attitude of rejection towards the use of urban microspace among buildings within urban developments - urban complexes - . Usually, these complexes admit solutions that apparently do not contribute to the achievement of common leisure activities in the resident dwellers. Therefore, the main purpose of this research is to deepen in the urban - environmental - social issue and urban design linked to the local morphological particularity, microclimate conditions, use of microspace and users’ requirements. In order to develop microclimate control strategies of microspace among buildings in hot - humid climate to look for optimal solutions that satisfy users’ needs of outdoors spaces in these residential areas. The research focuses in the study of contextual particularities related to microclimate and urban - morphotypological characteristics. Basically, microclimate (sunlight and ventilation), morphological and building factors as well as road surface characteristics. According to the proposed objective, this research is developed in four phases: the first one considers documentary review, relevant literature and researches related to environmental quality, social environment, physical environment, urban microspace, control and sustainable design, project modelling and sustainable strategies; while the second phase refers to contextual framework, urban characteristics, local climate data, plans and urban processes, typologies and urban structure. In this phase, the process of selection, analysis and urban - environmental evaluation of case studies (residential complexes) is described. The third phase approaches the assessment framework and case studies, physical and climate considerations as well as environmental - thermal evaluation of selected residential complexes. In this phase, statistical techniques and computational simulations are applied. Likewise, results obtained are analysed. Similarly, fourth and proposing phase includes the establishment of strategies, principles and guidelines of thermal optimization and partial conclusions of the thesis, scopes and future perspectives are exposed. Finally, from the results obtained, it is demonstrated that the analysis on reality experiences allow proving that situations and substantial environmental changes, levels of thermal affectations, comfort conditions and impact derive from urban characteristics, microspace components and from climate conditions which affect the development of activities and the effective use of microspace among buildings. The analysis of incidental morpho - climate factors and the study of interaction effects contribute to the establishment of principles and guidelines for the assessment and sustainable design of microspace among buildings as well as the correct use of climate elements in these urban areas oriented to social and leisure activities of resident population.

Aerodynamic Optimization of High-Speed Trains Nose using a Genetic Algorithm and Artificial Neural Network

An aerodynamic optimization of the train aerodynamic characteristics in term of front wind action sensitivity is carried out in this paper. In particular, a genetic algorithm (GA) is used to perform a shape optimization study of a high-speed train nose. The nose is parametrically defined via Bézier Curves, including a wider range of geometries in the design space as possible optimal solutions. Using a GA, the main disadvantage to deal with is the large number of evaluations need before finding such optimal. Here it is proposed the use of metamodels to replace Navier-Stokes solver. Among all the posibilities, Rsponse Surface Models and Artificial Neural Networks (ANN) are considered. Best results of prediction and generalization are obtained with ANN and those are applied in GA code. The paper shows the feasibility of using GA in combination with ANN for this problem, and solutions achieved are included.

A review on probabilistic graphical models in evolutionary computation

Thanks to their inherent properties, probabilistic graphical models are one of the prime candidates for machine learning and decision making tasks especially in uncertain domains. Their capabilities, like representation, inference and learning, if used effectively, can greatly help to build intelligent systems that are able to act accordingly in different problem domains. Evolutionary algorithms is one such discipline that has employed probabilistic graphical models to improve the search for optimal solutions in complex problems. This paper shows how probabilistic graphical models have been used in evolutionary algorithms to improve their performance in solving complex problems. Specifically, we give a survey of probabilistic model building-based evolutionary algorithms, called estimation of distribution algorithms, and compare different methods for probabilistic modeling in these algorithms.

Cross-entropy optimization for scaling factors of a fuzzy controller: a see-and-avoid approach for unmanned aerial systems

The Cross-Entropy (CE) is an efficient method for the estimation of rare-event probabilities and combinatorial optimization. This work presents a novel approach of the CE for optimization of a Soft-Computing controller. A Fuzzy controller was designed to command an unmanned aerial system (UAS) for avoiding collision task. The only sensor used to accomplish this task was a forward camera. The CE is used to reach a near-optimal controller by modifying the scaling factors of the controller inputs. The optimization was realized using the ROS-Gazebo simulation system. In order to evaluate the optimization a big amount of tests were carried out with a real quadcopter.

Vanadium-Doped In and Sn Sulphides: Photocatalysts able to use the whole visible light spectrum

Using photocatalysis for energy applications depends, more than for environmental purposes or selective chemical synthesis, on converting as much of the solar spectrum as possible; the best photocatalyst, titania, is far from this. Many efforts are pursued to use better that spectrum in photocatalysis, by doping titania or using other materials (mainly oxides, nitrides and sulphides) to obtain a lower bandgap, even if this means decreasing the chemical potential of the electron-hole pairs. Here we introduce an alternative scheme, using an idea recently proposed for photovoltaics: the intermediate band (IB) materials. It consists in introducing in the gap of a semiconductor an intermediate level which, acting like a stepstone, allows an electron jumping from the valence band to the conduction band in two steps, each one absorbing one sub-bandgap photon. For this the IB must be partially filled, to allow both sub-bandgap transitions to proceed at comparable rates; must be made of delocalized states to minimize nonradiative recombination; and should not communicate electronically with the outer world. For photovoltaic use the optimum efficiency so achievable, over 1.5 times that given by a normal semiconductor, is obtained with an overall bandgap around 2.0 eV (which would be near-optimal also for water phtosplitting). Note that this scheme differs from the doping principle usually considered in photocatalysis, which just tries to decrease the bandgap; its aim is to keep the full bandgap chemical potential but using also lower energy photons. In the past we have proposed several IB materials based on extensively doping known semiconductors with light transition metals, checking first of all with quantum calculations that the desired IB structure results. Subsequently we have synthesized in powder form two of them: the thiospinel In2S3 and the layered compound SnS2 (having bandgaps of 2.0 and 2.2 eV respectively) where the octahedral cation is substituted at a â?10% level with vanadium, and we have verified that this substitution introduces in the absorption spectrum the sub-bandgap features predicted by the calculations. With these materials we have verified, using a simple reaction (formic acid oxidation), that the photocatalytic spectral response is indeed extended to longer wavelengths, being able to use even 700 nm photons, without largely degrading the response for above-bandgap photons (i.e. strong recombination is not induced) [3b, 4]. These materials are thus promising for efficient photoevolution of hydrogen from water; work on this is being pursued, the results of which will be presented.

New laser-based approaches to improve the passivation and rear contact quality in high effiency crystalline silicon solar cells

Laser processing has been the tool of choice last years to develop improved concepts in contact formation for high efficiency crystalline silicon (c-Si) solar cells. New concepts based on standard laser fired contacts (LFC) or advanced laser doping (LD) techniques are optimal solutions for both the front and back contacts of a number of structures with growing interest in the c-Si PV industry. Nowadays, substantial efforts are underway to optimize these processes in order to be applied industrially in high efficiency concepts. However a critical issue in these devices is that, most of them, demand a very low thermal input during the fabrication sequence and a minimal damage of the structure during the laser irradiation process. Keeping these two objectives in mind, in this work we discuss the possibility of using laser-based processes to contact the rear side of silicon heterojunction (SHJ) solar cells in an approach fully compatible with the low temperature processing associated to these devices. First we discuss the possibility of using standard LFC techniques in the fabrication of SHJ cells on p-type substrates, studying in detail the effect of the laser wavelength on the contact quality. Secondly, we present an alternative strategy bearing in mind that a real challenge in the rear contact formation is to reduce the damage induced by the laser irradiation. This new approach is based on local laser doping techniques previously developed by our groups, to contact the rear side of p-type c-Si solar cells by means of laser processing before rear metallization of dielectric stacks containing Al2O3. In this work we demonstrate the possibility of using this new approach in SHJ cells with a distinct advantage over other standard LFC techniques.

Aerodynamic Optimization of the Nose Shape of a High-speed Train

La influencia de la aerodinámica en el diseño de los trenes de alta velocidad, unida a la necesidad de resolver nuevos problemas surgidos con el aumento de la velocidad de circulación y la reducción de peso del vehículo, hace evidente el interés de plantear un estudio de optimización que aborde tales puntos. En este contexto, se presenta en esta tesis la optimización aerodinámica del testero de un tren de alta velocidad, llevada a cabo mediante el uso de métodos de optimización avanzados. Entre estos métodos, se ha elegido aquí a los algoritmos genéticos y al método adjunto como las herramientas para llevar a cabo dicha optimización. La base conceptual, las características y la implementación de los mismos se detalla a lo largo de la tesis, permitiendo entender los motivos de su elección, y las consecuencias, en términos de ventajas y desventajas que cada uno de ellos implican. El uso de los algorimos genéticos implica a su vez la necesidad de una parametrización geométrica de los candidatos a óptimo y la generación de un modelo aproximado que complementa al método de optimización. Estos puntos se describen de modo particular en el primer bloque de la tesis, enfocada a la metodología seguida en este estudio. El segundo bloque se centra en la aplicación de los métodos a fin de optimizar el comportamiento aerodinámico del tren en distintos escenarios. Estos escenarios engloban los casos más comunes y también algunos de los más exigentes a los que hace frente un tren de alta velocidad: circulación en campo abierto con viento frontal o viento lateral, y entrada en túnel. Considerando el caso de viento frontal en campo abierto, los dos métodos han sido aplicados, permitiendo una comparación de las diferentes metodologías, así como el coste computacional asociado a cada uno, y la minimización de la resistencia aerodinámica conseguida en esa optimización. La posibilidad de evitar parametrizar la geometría y, por tanto, reducir el coste computacional del proceso de optimización es la característica más significativa de los métodos adjuntos, mientras que en el caso de los algoritmos genéticos se destaca la simplicidad y capacidad de encontrar un óptimo global en un espacio de diseño multi-modal o de resolver problemas multi-objetivo. El caso de viento lateral en campo abierto considera nuevamente los dos métoxi dos de optimización anteriores. La parametrización se ha simplificado en este estudio, lo que notablemente reduce el coste numérico de todo el estudio de optimización, a la vez que aún recoge las características geométricas más relevantes en un tren de alta velocidad. Este análisis ha permitido identificar y cuantificar la influencia de cada uno de los parámetros geométricos incluídos en la parametrización, y se ha observado que el diseño de la arista superior a barlovento es fundamental, siendo su influencia mayor que la longitud del testero o que la sección frontal del mismo. Finalmente, se ha considerado un escenario más a fin de validar estos métodos y su capacidad de encontrar un óptimo global. La entrada de un tren de alta velocidad en un túnel es uno de los casos más exigentes para un tren por el pico de sobrepresión generado, el cual afecta a la confortabilidad del pasajero, así como a la estabilidad del vehículo y al entorno próximo a la salida del túnel. Además de este problema, otro objetivo a minimizar es la resistencia aerodinámica, notablemente superior al caso de campo abierto. Este problema se resuelve usando algoritmos genéticos. Dicho método permite obtener un frente de Pareto donde se incluyen el conjunto de óptimos que minimizan ambos objetivos. ABSTRACT Aerodynamic design of trains influences several aspects of high-speed trains performance in a very significant level. In this situation, considering also that new aerodynamic problems have arisen due to the increase of the cruise speed and lightness of the vehicle, it is evident the necessity of proposing an optimization study concerning the train aerodynamics. Thus, the aerodynamic optimization of the nose shape of a high-speed train is presented in this thesis. This optimization is based on advanced optimization methods. Among these methods, genetic algorithms and the adjoint method have been selected. A theoretical description of their bases, the characteristics and the implementation of each method is detailed in this thesis. This introduction permits understanding the causes of their selection, and the advantages and drawbacks of their application. The genetic algorithms requirethe geometrical parameterization of any optimal candidate and the generation of a metamodel or surrogate model that complete the optimization process. These points are addressed with a special attention in the first block of the thesis, focused on the methodology considered in this study. The second block is referred to the use of these methods with the purpose of optimizing the aerodynamic performance of a high-speed train in several scenarios. These scenarios englobe the most representative operating conditions of high-speed trains, and also some of the most exigent train aerodynamic problems: front wind and cross-wind situations in open air, and the entrance of a high-speed train in a tunnel. The genetic algorithms and the adjoint method have been applied in the minimization of the aerodynamic drag on the train with front wind in open air. The comparison of these methods allows to evaluate the methdology and computational cost of each one, as well as the resulting minimization of the aerodynamic drag. Simplicity and robustness, the straightforward realization of a multi-objective optimization, and the capability of searching a global optimum are the main attributes of genetic algorithm. However, the requirement of geometrically parameterize any optimal candidate is a significant drawback that is avoided with the use of the adjoint method. This independence of the number of design variables leads to a relevant reduction of the pre-processing and computational cost. Considering the cross-wind stability, both methods are used again for the minimization of the side force. In this case, a simplification of the geometric parameterization of the train nose is adopted, what dramatically reduces the computational cost of the optimization process. Nevertheless, some of the most important geometrical characteristics are still described with this simplified parameterization. This analysis identifies and quantifies the influence of each design variable on the side force on the train. It is observed that the A-pillar roundness is the most demanding design parameter, with a more important effect than the nose length or the train cross-section area. Finally, a third scenario is considered for the validation of these methods in the aerodynamic optimization of a high-speed train. The entrance of a train in a tunnel is one of the most exigent train aerodynamic problems. The aerodynamic consequences of high-speed trains running in a tunnel are basically resumed in two correlated phenomena, the generation of pressure waves and an increase in aerodynamic drag. This multi-objective optimization problem is solved with genetic algorithms. The result is a Pareto front where a set of optimal solutions that minimize both objectives.

A multi-criteria optimization and decision-making approach for improvement of food engineering processes.

The objective of this study was to propose a multi-criteria optimization and decision-making technique to solve food engineering problems. This technique was demostrated using experimental data obtained on osmotic dehydratation of carrot cubes in a sodium chloride solution. The Aggregating Functions Approach, the Adaptive Random Search Algorithm, and the Penalty Functions Approach were used in this study to compute the initial set of non-dominated or Pareto-optimal solutions. Multiple non-linear regression analysis was performed on a set of experimental data in order to obtain particular multi-objective functions (responses), namely water loss, solute gain, rehydration ratio, three different colour criteria of rehydrated product, and sensory evaluation (organoleptic quality). Two multi-criteria decision-making approaches, the Analytic Hierarchy Process (AHP) and the Tabular Method (TM), were used simultaneously to choose the best alternative among the set of non-dominated solutions. The multi-criteria optimization and decision-making technique proposed in this study can facilitate the assessment of criteria weights, giving rise to a fairer, more consistent, and adequate final compromised solution or food process. This technique can be useful to food scientists in research and education, as well as to engineers involved in the improvement of a variety of food engineering processes.

Laser Processes for Contact Optimization in c-Si Solar Cells

Solid State Lasers (SSL) have been used in microelectronic and photovoltaic (PV) industry for decades but, currently, laser technology appears as a key enabling technology to improve efficiency and to reduce production costs in high efficiency solar cells fabrication. Moreover, the fact that the interaction between the laser radiation and the device is normally localized and restricted to a controlled volume makes SSL a tool of choice for the implementation of low temperature concepts in PV industry. Specifically, SSL are ideally suited to improve the electrical performance of the contacts further improving the efficiency of these devices. Advanced concepts based on standard laser firing or advanced laser doping techniques are optimal solutions for the back contact of a significant number of structures of growing interest in the c-Si PV industry, and a number of solutions has been proposed as well for emitter formation, to reduce the metallization optical losses or even to remove completely the contacts from the front part of the cell. In this work we present our more recent results of SSL applications for contact optimization in c-Si solar cell technology, including applications on low temperature processes demanding devices, like heterojunction solar cells.

Demystifying the information reconciliation protocol cascade

Cascade is an information reconciliation protocol proposed in the context of secret key agreement in quantum cryptography. This protocol allows removing discrepancies in two partially correlated sequences that belong to distant parties, connected through a public noiseless channel. It is highly interactive, thus requiring a large number of channel communications between the parties to proceed and, although its efficiency is not optimal, it has become the de-facto standard for practical implementations of information reconciliation in quantum key distribution. The aim of this work is to analyze the performance of Cascade, to discuss its strengths, weaknesses and optimization possibilities, comparing with some of the modified versions that have been proposed in the literature. When looking at all design trade-offs, a new view emerges that allows to put forward a number of guidelines and propose near optimal parameters for the practical implementation of Cascade improving performance significantly in comparison with all previous proposals.

On the layout of a least weight single span structure with uniform load. Some comments and improvements

Beghini et al (Struct Multidisc Optim doi:10.1007/s00158-013-1030-6, 2013) have published a very interesting paper arriving to practically the same nearly optimal solutions for the so named “bridge prob- lem” that the Writers published a year before, but using an alternative and remarkable approach to the problem. In spite of this general agreement, the Writers think that some details of the paper can be improved and there are results that can be given a clear and mean- ingful interpretation thanks to an old and practically unknown theorem on optimal slenderness.

Mathematical foundations for efficient structural controllability and observability analysis of complex systems

The relationship between structural controllability and observability of complex systems is studied. Algebraic and graph theoretic tools are combined to prove the extent of some controller/observer duality results. Two types of control design problems are addressed and some fundamental theoretical results are provided. In addition new algorithms are presented to compute optimal solutions for monitoring large scale real networks.

Power-Aware Multi-Objective Evolvable Hardware System on an FPGA

Dynamic and Partial Reconfiguration (DPR) allows a system to be able to modify certain parts of itself during run-time. This feature gives rise to the capability of evolution: changing parts of the configuration according to the online evaluation of performance or other parameters. The evolution is achieved through a bio-inspired model in which the features of the system are identified as genes. The objective of the evolution may not be a single one; in this work, power consumption is taken into consideration, together with the quality of filtering, as the measure of performance, of a noisy image. Pareto optimality is applied to the evolutionary process, in order to find a representative set of optimal solutions as for performance and power consumption. The main contributions of this paper are: implementing an evolvable system on a low-power Spartan-6 FPGA included in a Wireless Sensor Network node and, by enabling the availability of a real measure of power consumption at run-time, achieving the capability of multi-objective evolution, that yields different optimal configurations, among which the selected one will depend on the relative “weights” of performance and power consumption.