Optimized design of the prestress in continuous bridge decks

In this paper a method for automatic design of the prestress in continuous bridge decks is presented. In a first step of the procedure the optimal prestressed force for a completely geometrically defined and feasible prestress layout is obtained by means of linear programming techniques. Further on, in a second step the prestress geometry and minimum force are automatically found by steepest descent optimization techniques. Finally this methodology is applied to two-span continuous bridge decks and from the obtained results some preliminary design rules can be drawn.

Inteligencia artificial para la predicción y control del acabado superficial en procesos de fresado a alta velocidad

El objetivo principal de esta tesis doctoral es profundizar en el análisis y diseño de un sistema inteligente para la predicción y control del acabado superficial en un proceso de fresado a alta velocidad, basado fundamentalmente en clasificadores Bayesianos, con el prop´osito de desarrollar una metodolog´ıa que facilite el diseño de este tipo de sistemas. El sistema, cuyo propósito es posibilitar la predicción y control de la rugosidad superficial, se compone de un modelo aprendido a partir de datos experimentales con redes Bayesianas, que ayudar´a a comprender los procesos dinámicos involucrados en el mecanizado y las interacciones entre las variables relevantes. Dado que las redes neuronales artificiales son modelos ampliamente utilizados en procesos de corte de materiales, también se incluye un modelo para fresado usándolas, donde se introdujo la geometría y la dureza del material como variables novedosas hasta ahora no estudiadas en este contexto. Por lo tanto, una importante contribución en esta tesis son estos dos modelos para la predicción de la rugosidad superficial, que se comparan con respecto a diferentes aspectos: la influencia de las nuevas variables, los indicadores de evaluación del desempeño, interpretabilidad. Uno de los principales problemas en la modelización con clasificadores Bayesianos es la comprensión de las enormes tablas de probabilidad a posteriori producidas. Introducimos un m´etodo de explicación que genera un conjunto de reglas obtenidas de árboles de decisión. Estos árboles son inducidos a partir de un conjunto de datos simulados generados de las probabilidades a posteriori de la variable clase, calculadas con la red Bayesiana aprendida a partir de un conjunto de datos de entrenamiento. Por último, contribuimos en el campo multiobjetivo en el caso de que algunos de los objetivos no se puedan cuantificar en números reales, sino como funciones en intervalo de valores. Esto ocurre a menudo en aplicaciones de aprendizaje automático, especialmente las basadas en clasificación supervisada. En concreto, se extienden las ideas de dominancia y frontera de Pareto a esta situación. Su aplicación a los estudios de predicción de la rugosidad superficial en el caso de maximizar al mismo tiempo la sensibilidad y la especificidad del clasificador inducido de la red Bayesiana, y no solo maximizar la tasa de clasificación correcta. Los intervalos de estos dos objetivos provienen de un m´etodo de estimación honesta de ambos objetivos, como e.g. validación cruzada en k rodajas o bootstrap.---ABSTRACT---The main objective of this PhD Thesis is to go more deeply into the analysis and design of an intelligent system for surface roughness prediction and control in the end-milling machining process, based fundamentally on Bayesian network classifiers, with the aim of developing a methodology that makes easier the design of this type of systems. The system, whose purpose is to make possible the surface roughness prediction and control, consists of a model learnt from experimental data with the aid of Bayesian networks, that will help to understand the dynamic processes involved in the machining and the interactions among the relevant variables. Since artificial neural networks are models widely used in material cutting proceses, we include also an end-milling model using them, where the geometry and hardness of the piecework are introduced as novel variables not studied so far within this context. Thus, an important contribution in this thesis is these two models for surface roughness prediction, that are then compared with respecto to different aspects: influence of the new variables, performance evaluation metrics, interpretability. One of the main problems with Bayesian classifier-based modelling is the understanding of the enormous posterior probabilitiy tables produced. We introduce an explanation method that generates a set of rules obtained from decision trees. Such trees are induced from a simulated data set generated from the posterior probabilities of the class variable, calculated with the Bayesian network learned from a training data set. Finally, we contribute in the multi-objective field in the case that some of the objectives cannot be quantified as real numbers but as interval-valued functions. This often occurs in machine learning applications, especially those based on supervised classification. Specifically, the dominance and Pareto front ideas are extended to this setting. Its application to the surface roughness prediction studies the case of maximizing simultaneously the sensitivity and specificity of the induced Bayesian network classifier, rather than only maximizing the correct classification rate. Intervals in these two objectives come from a honest estimation method of both objectives, like e.g. k-fold cross-validation or bootstrap.

Aportación al análisis de espectros de radiación: estructuras y algoritmos

A lo largo del presente trabajo se investiga la viabilidad de la descomposición automática de espectros de radiación gamma por medio de algoritmos de resolución de sistemas de ecuaciones algebraicas lineales basados en técnicas de pseudoinversión. La determinación de dichos algoritmos ha sido realizada teniendo en cuenta su posible implementación sobre procesadores de propósito específico de baja complejidad. En el primer capítulo se resumen las técnicas para la detección y medida de la radiación gamma que han servido de base para la confección de los espectros tratados en el trabajo. Se reexaminan los conceptos asociados con la naturaleza de la radiación electromagnética, así como los procesos físicos y el tratamiento electrónico que se hallan involucrados en su detección, poniendo de relieve la naturaleza intrínsecamente estadística del proceso de formación del espectro asociado como una clasificación del número de detecciones realizadas en función de la energía supuestamente continua asociada a las mismas. Para ello se aporta una breve descripción de los principales fenómenos de interacción de la radiación con la materia, que condicionan el proceso de detección y formación del espectro. El detector de radiación es considerado el elemento crítico del sistema de medida, puesto que condiciona fuertemente el proceso de detección. Por ello se examinan los principales tipos de detectores, con especial hincapié en los detectores de tipo semiconductor, ya que son los más utilizados en la actualidad. Finalmente, se describen los subsistemas electrónicos fundamentales para el acondicionamiento y pretratamiento de la señal procedente del detector, a la que se le denomina con el término tradicionalmente utilizado de Electrónica Nuclear. En lo que concierne a la espectroscopia, el principal subsistema de interés para el presente trabajo es el analizador multicanal, el cual lleva a cabo el tratamiento cualitativo de la señal, y construye un histograma de intensidad de radiación en el margen de energías al que el detector es sensible. Este vector N-dimensional es lo que generalmente se conoce con el nombre de espectro de radiación. Los distintos radionúclidos que participan en una fuente de radiación no pura dejan su impronta en dicho espectro. En el capítulo segundo se realiza una revisión exhaustiva de los métodos matemáticos en uso hasta el momento ideados para la identificación de los radionúclidos presentes en un espectro compuesto, así como para determinar sus actividades relativas. Uno de ellos es el denominado de regresión lineal múltiple, que se propone como la aproximación más apropiada a los condicionamientos y restricciones del problema: capacidad para tratar con espectros de baja resolución, ausencia del concurso de un operador humano (no supervisión), y posibilidad de ser soportado por algoritmos de baja complejidad capaces de ser instrumentados sobre procesadores dedicados de alta escala de integración. El problema del análisis se plantea formalmente en el tercer capítulo siguiendo las pautas arriba mencionadas y se demuestra que el citado problema admite una solución en la teoría de memorias asociativas lineales. Un operador basado en este tipo de estructuras puede proporcionar la solución al problema de la descomposición espectral deseada. En el mismo contexto, se proponen un par de algoritmos adaptativos complementarios para la construcción del operador, que gozan de unas características aritméticas especialmente apropiadas para su instrumentación sobre procesadores de alta escala de integración. La característica de adaptatividad dota a la memoria asociativa de una gran flexibilidad en lo que se refiere a la incorporación de nueva información en forma progresiva.En el capítulo cuarto se trata con un nuevo problema añadido, de índole altamente compleja. Es el del tratamiento de las deformaciones que introducen en el espectro las derivas instrumentales presentes en el dispositivo detector y en la electrónica de preacondicionamiento. Estas deformaciones invalidan el modelo de regresión lineal utilizado para describir el espectro problema. Se deriva entonces un modelo que incluya las citadas deformaciones como una ampliación de contribuciones en el espectro compuesto, el cual conlleva una ampliación sencilla de la memoria asociativa capaz de tolerar las derivas en la mezcla problema y de llevar a cabo un análisis robusto de contribuciones. El método de ampliación utilizado se basa en la suposición de pequeñas perturbaciones. La práctica en el laboratorio demuestra que, en ocasiones, las derivas instrumentales pueden provocar distorsiones severas en el espectro que no pueden ser tratadas por el modelo anterior. Por ello, en el capítulo quinto se plantea el problema de medidas afectadas por fuertes derivas desde el punto de vista de la teoría de optimización no lineal. Esta reformulación lleva a la introducción de un algoritmo de tipo recursivo inspirado en el de Gauss-Newton que permite introducir el concepto de memoria lineal realimentada. Este operador ofrece una capacidad sensiblemente mejorada para la descomposición de mezclas con fuerte deriva sin la excesiva carga computacional que presentan los algoritmos clásicos de optimización no lineal. El trabajo finaliza con una discusión de los resultados obtenidos en los tres principales niveles de estudio abordados, que se ofrecen en los capítulos tercero, cuarto y quinto, así como con la elevación a definitivas de las principales conclusiones derivadas del estudio y con el desglose de las posibles líneas de continuación del presente trabajo.---ABSTRACT---Through the present research, the feasibility of Automatic Gamma-Radiation Spectral Decomposition by Linear Algebraic Equation-Solving Algorithms using Pseudo-Inverse Techniques is explored. The design of the before mentioned algorithms has been done having into account their possible implementation on Specific-Purpose Processors of Low Complexity. In the first chapter, the techniques for the detection and measurement of gamma radiation employed to construct the spectra being used throughout the research are reviewed. Similarly, the basic concepts related with the nature and properties of the hard electromagnetic radiation are also re-examined, together with the physic and electronic processes involved in the detection of such kind of radiation, with special emphasis in the intrinsic statistical nature of the spectrum build-up process, which is considered as a classification of the number of individual photon-detections as a function of the energy associated to each individual photon. Fbr such, a brief description of the most important matter-energy interaction phenomena conditioning the detection and spectrum formation processes is given. The radiation detector is considered as the most critical element in the measurement system, as this device strongly conditions the detection process. Fbr this reason, the characteristics of the most frequent detectors are re-examined, with special emphasis on those of semiconductor nature, as these are the most frequently employed ones nowadays. Finally, the fundamental electronic subsystems for preaconditioning and treating of the signal delivered by the detector, classically addresed as Nuclear Electronics, is described. As far as Spectroscopy is concerned, the subsystem most interesting for the scope covered by the present research is the so-called Multichannel Analyzer, which is devoted to the cualitative treatment of the signal, building-up a hystogram of radiation intensity in the range of energies in which the detector is sensitive. The resulting N-dimensional vector is generally known with the ñame of Radiation Spectrum. The different radio-nuclides contributing to the spectrum of a composite source will leave their fingerprint in the resulting spectrum. Through the second chapter, an exhaustive review of the mathematical methods devised to the present moment to identify the radio-nuclides present in the composite spectrum and to quantify their relative contributions, is reviewed. One of the more popular ones is the so-known Múltiple Linear Regression, which is proposed as the best suited approach according to the constraints and restrictions present in the formulation of the problem, i.e., the need to treat low-resolution spectra, the absence of control by a human operator (un-supervision), and the possibility of being implemented as low-complexity algorithms amenable of being supported by VLSI Specific Processors. The analysis problem is formally stated through the third chapter, following the hints established in this context, and it is shown that the addressed problem may be satisfactorily solved under the point of view of Linear Associative Memories. An operator based on this kind of structures may provide the solution to the spectral decomposition problem posed. In the same context, a pair of complementary adaptive algorithms useful for the construction of the solving operator are proposed, which share certain special arithmetic characteristics that render them specially suitable for their implementation on VLSI Processors. The adaptive nature of the associative memory provides a high flexibility to this operator, in what refers to the progressive inclusión of new information to the knowledge base. Through the fourth chapter, this fact is treated together with a new problem to be considered, of a high interest but quite complex nature, as is the treatment of the deformations appearing in the spectrum when instrumental drifts in both the detecting device and the pre-acconditioning electronics are to be taken into account. These deformations render the Linear Regression Model proposed almost unuseful to describe the resulting spectrum. A new model including the drifts is derived as an extensión of the individual contributions to the composite spectrum, which implies a simple extensión of the Associative Memory, which renders this suitable to accept the drifts in the composite spectrum, thus producing a robust analysis of contributions. The extensión method is based on the Low-Amplitude Perturbation Hypothesis. Experimental practice shows that in certain cases the instrumental drifts may provoke severe distortions in the resulting spectrum, which can not be treated with the before-mentioned hypothesis. To cover also these less-frequent cases, through the fifth chapter, the problem involving strong drifts is treated under the point of view of Non-Linear Optimization Techniques. This reformulation carries the study to the consideration of recursive algorithms based on the Gauss-Newton methods, which allow the introduction of Feed-Back Memories, computing elements with a sensibly improved capability to decompose spectra affected by strong drifts. The research concludes with a discussion of the results obtained in the three main levéis of study considerad, which are presented in chapters third, fourth and fifth, toghether with the review of the main conclusions derived from the study and the outline of the main research lines opened by the present work.

Contribución al análisis eficiente y a la mejora de prestaciones de antenas reflectarray

El diseño de una antena reflectarray bajo la aproximación de periodicidad local requiere la determinación de la matriz de scattering de estructuras multicapa con metalizaciones periódicas para un gran número de geometrías diferentes. Por lo tanto, a la hora de diseñar antenas reflectarray en tiempos de CPU razonables, se necesitan herramientas númericas rápidas y precisas para el análisis de las estructuras periódicas multicapa. En esta tesis se aplica la versión Galerkin del Método de los Momentos (MDM) en el dominio espectral al análisis de las estructuras periódicas multicapa necesarias para el diseño de antenas reflectarray basadas en parches apilados o en dipolos paralelos coplanares. Desgraciadamente, la aplicación de este método numérico involucra el cálculo de series dobles infinitas, y mientras que algunas series convergen muy rápidamente, otras lo hacen muy lentamente. Para aliviar este problema, en esta tesis se propone un novedoso MDM espectral-espacial para el análisis de las estructuras periódicas multicapa, en el cual las series rápidamente convergente se calculan en el dominio espectral, y las series lentamente convergentes se calculan en el dominio espacial mediante una versión mejorada de la formulación de ecuaciones integrales de potenciales mixtos (EIPM) del MDM. Esta versión mejorada se basa en la interpolación eficiente de las funciones de Green multicapa periódicas, y en el cálculo eficiente de las integrales singulares que conducen a los elementos de la matriz del MDM. El novedoso método híbrido espectral-espacial y el tradicional MDM en el dominio espectral se han comparado en el caso de los elementos reflectarray basado en parches apilados. Las simulaciones numéricas han demostrado que el tiempo de CPU requerido por el MDM híbrido es alrededor de unas 60 veces más rápido que el requerido por el tradicional MDM en el dominio espectral para una precisión de dos cifras significativas. El uso combinado de elementos reflectarray con parches apilados y técnicas de optimización de banda ancha ha hecho posible diseñar antenas reflectarray de transmisiónrecepción (Tx-Rx) y polarización dual para aplicaciones de espacio con requisitos muy restrictivos. Desgraciadamente, el nivel de aislamiento entre las polarizaciones ortogonales en antenas DBS (típicamente 30 dB) es demasiado exigente para ser conseguido con las antenas basadas en parches apilados. Además, el uso de elementos reflectarray con parches apilados conlleva procesos de fabricación complejos y costosos. En esta tesis se investigan varias configuraciones de elementos reflectarray basadas en conjuntos de dipolos paralelos con el fin de superar los inconvenientes que presenta el elemento basado en parches apilados. Primeramente, se propone un elemento consistente en dos conjuntos apilados ortogonales de tres dipolos paralelos para aplicaciones de polarización dual. Se ha diseñado, fabricado y medido una antena basada en este elemento, y los resultados obtenidos para la antena indican que tiene unas altas prestaciones en términos de ancho de banda, pérdidas, eficiencia y discriminación contrapolar, además de requerir un proceso de fabricación mucho más sencillo que el de las antenas basadas en tres parches apilados. Desgraciadamente, el elemento basado en dos conjuntos ortogonales de tres dipolos paralelos no proporciona suficientes grados de libertad para diseñar antenas reflectarray de transmisión-recepción (Tx-Rx) de polarización dual para aplicaciones de espacio por medio de técnicas de optimización de banda ancha. Por este motivo, en la tesis se propone un nuevo elemento reflectarray que proporciona los grados de libertad suficientes para cada polarización. El nuevo elemento consiste en dos conjuntos ortogonales de cuatro dipolos paralelos. Cada conjunto contiene tres dipolos coplanares y un dipolo apilado. Para poder acomodar los dos conjuntos de dipolos en una sola celda de la antena reflectarray, el conjunto de dipolos de una polarización está desplazado medio período con respecto al conjunto de dipolos de la otra polarización. Este hecho permite usar solamente dos niveles de metalización para cada elemento de la antena, lo cual simplifica el proceso de fabricación como en el caso del elemento basados en dos conjuntos de tres dipolos paralelos coplanares. Una antena de doble polarización y doble banda (Tx-Rx) basada en el nuevo elemento ha sido diseñada, fabricada y medida. La antena muestra muy buenas presentaciones en las dos bandas de frecuencia con muy bajos niveles de polarización cruzada. Simulaciones numéricas presentadas en la tesis muestran que estos bajos de niveles de polarización cruzada se pueden reducir todavía más si se llevan a cabo pequeñas rotaciones de los dos conjuntos de dipolos asociados a cada polarización. ABSTRACT The design of a reflectarray antenna under the local periodicity assumption requires the determination of the scattering matrix of a multilayered structure with periodic metallizations for quite a large number of different geometries. Therefore, in order to design reflectarray antennas within reasonable CPU times, fast and accurate numerical tools for the analysis of the periodic multilayered structures are required. In this thesis the Galerkin’s version of the Method of Moments (MoM) in the spectral domain is applied to the analysis of the periodic multilayered structures involved in the design of reflectarray antennas made of either stacked patches or coplanar parallel dipoles. Unfortunately, this numerical approach involves the computation of double infinite summations, and whereas some of these summations converge very fast, some others converge very slowly. In order to alleviate this problem, in the thesis a novel hybrid MoM spectral-spatial domain approach is proposed for the analysis of the periodic multilayered structures. In the novel approach, whereas the fast convergent summations are computed in the spectral domain, the slowly convergent summations are computed by means of an enhanced Mixed Potential Integral Equation (MPIE) formulation of the MoM in the spatial domain. This enhanced formulation is based on the efficient interpolation of the multilayered periodic Green’s functions, and on the efficient computation of the singular integrals leading to the MoM matrix entries. The novel hybrid spectral-spatial MoM code and the standard spectral domain MoM code have both been compared in the case of reflectarray elements based on multilayered stacked patches. Numerical simulations have shown that the CPU time required by the hybrid MoM is around 60 times smaller than that required by the standard spectral MoM for an accuracy of two significant figures. The combined use of reflectarray elements based on stacked patches and wideband optimization techniques has made it possible to design dual polarization transmit-receive (Tx-Rx) reflectarrays for space applications with stringent requirements. Unfortunately, the required level of isolation between orthogonal polarizations in DBS antennas (typically 30 dB) is hard to achieve with the configuration of stacked patches. Moreover, the use of reflectarrays based on stacked patches leads to a complex and expensive manufacturing process. In this thesis, we investigate several configurations of reflectarray elements based on sets of parallel dipoles that try to overcome the drawbacks introduced by the element based on stacked patches. First, an element based on two stacked orthogonal sets of three coplanar parallel dipoles is proposed for dual polarization applications. An antenna made of this element has been designed, manufactured and measured, and the results obtained show that the antenna presents a high performance in terms of bandwidth, losses, efficiency and cross-polarization discrimination, while the manufacturing process is cheaper and simpler than that of the antennas made of stacked patches. Unfortunately, the element based on two sets of three coplanar parallel dipoles does not provide enough degrees of freedom to design dual-polarization transmit-receive (Tx-Rx) reflectarray antennas for space applications by means of wideband optimization techniques. For this reason, in the thesis a new reflectarray element is proposed which does provide enough degrees of freedom for each polarization. This new element consists of two orthogonal sets of four parallel dipoles, each set containing three coplanar dipoles and one stacked dipole. In order to accommodate the two sets of dipoles in each reflectarray cell, the set of dipoles for one polarization is shifted half a period from the set of dipoles for the other polarization. This also makes it possible to use only two levels of metallization for the reflectarray element, which simplifies the manufacturing process as in the case of the reflectarray element based on two sets of three parallel dipoles. A dual polarization dual-band (Tx-Rx) reflectarray antenna based on the new element has been designed, manufactured and measured. The antenna shows a very good performance in both Tx and Rx frequency bands with very low levels of cross-polarization. Numerical simulations carried out in the thesis have shown that the low levels of cross-polarization can be even made smaller by means of small rotations of the two sets of dipoles associated to each polarization.

Simultaneous environmental and economic process synthesis of Isobutane Alkylation

This multidisciplinary study concerns the optimal design of processes with a view to both maximizing profit and minimizing environmental impacts. This can be achieved by a combination of traditional chemical process design methods, measurements of environmental impacts and advanced mathematical optimization techniques. More to the point, this paper presents a hybrid simulation-multiobjective optimization approach that at once optimizes the production cost and minimizes the associated environmental impacts of isobutane alkylation. This approach has also made it possible to obtain the flowsheet configurations and process variables that are needed to manufacture isooctane in a way that satisfies the above-stated double aim. The problem is formulated as a Generalized Disjunctive Programming problem and solved using state-of-the-art logic-based algorithms. It is shown, starting from existing alternatives for the process, that it is possible to systematically generate a superstructure that includes alternatives not previously considered. The optimal solution, in the form a Pareto curve, includes different structural alternatives from which the most suitable design can be selected. To evaluate the environmental impact, Life Cycle Assessment based on two different indicators is employed: Ecoindicator 99 and Global Warming Potential.

Operations and Planning in Sustainable Power Systems

Thesis (Ph.D.)--University of Washington, 2016-06

A tutorial on the cross-entropy method

The cross-entropy (CE) method is a new generic approach to combinatorial and multi-extremal optimization and rare event simulation. The purpose of this tutorial is to give a gentle introduction to the CE method. We present the CE methodology, the basic algorithm and its modifications, and discuss applications in combinatorial optimization and machine learning. combinatorial optimization

A cognitive genetic algorithm for power distribution system planning

Power systems are large scale nonlinear systems with high complexity. Various optimization techniques and expert systems have been used in power system planning. However, there are always some factors that cannot be quantified, modeled, or even expressed by expert systems. Moreover, such planning problems are often large scale optimization problems. Although computational algorithms that are capable of handling large dimensional problems can be used, the computational costs are still very high. To solve these problems, in this paper, investigation is made to explore the efficiency and effectiveness of combining mathematic algorithms with human intelligence. It had been discovered that humans can join the decision making progresses by cognitive feedback. Based on cognitive feedback and genetic algorithm, a new algorithm called cognitive genetic algorithm is presented. This algorithm can clarify and extract human's cognition. As an important application of this cognitive genetic algorithm, a practical decision method for power distribution system planning is proposed. By using this decision method, the optimal results that satisfy human expertise can be obtained and the limitations of human experts can be minimized in the mean time.

Optimizing the data intensive mediator-based Web services composition

Effectively using heterogeneous, distributed information has attracted much research in recent years. Current web services technologies have been used successfully in some non data intensive distributed prototype systems. However, most of them can not work well in data intensive environment. This paper provides an infrastructure layer in data intensive environment for the effectively providing spatial information services by using the web services over the Internet. We extensively investigate and analyze the overhead of web services in data intensive environment, and propose some new optimization techniques which can greatly increase the system’s efficiency. Our experiments show that these techniques are suitable to data intensive environment. Finally, we present the requirement of these techniques for the information of web services over the Internet.

Selecting the most preferable alternatives in a group decision making problem using DEA

Group decision making is the study of identifying and selecting alternatives based on the values and preferences of the decision maker. Making a decision implies that there are several alternative choices to be considered. This paper uses the concept of Data Envelopment Analysis to introduce a new mathematical method for selecting the best alternative in a group decision making environment. The introduced model is a multi-objective function which is converted into a multi-objective linear programming model from which the optimal solution is obtained. A numerical example shows how the new model can be applied to rank the alternatives or to choose a subset of the most promising alternatives.

Ranking efficient decision-making units in data envelopment analysis using fuzzy concept

This paper introduces a new mathematical method for improving the discrimination power of data envelopment analysis and to completely rank the efficient decision-making units (DMUs). Fuzzy concept is utilised. For this purpose, first all DMUs are evaluated with the CCR model. Thereafter, the resulted weights for each output are considered as fuzzy sets and are then converted to fuzzy numbers. The introduced model is a multi-objective linear model, endpoints of which are the highest and lowest of the weighted values. An added advantage of the model is its ability to handle the infeasibility situation sometimes faced by previously introduced models.

Fuzzy data envelopment analysis:a discrete approach

Data envelopment analysis (DEA) as introduced by Charnes, Cooper, and Rhodes (1978) is a linear programming technique that has widely been used to evaluate the relative efficiency of a set of homogenous decision making units (DMUs). In many real applications, the input-output variables cannot be precisely measured. This is particularly important in assessing efficiency of DMUs using DEA, since the efficiency score of inefficient DMUs are very sensitive to possible data errors. Hence, several approaches have been proposed to deal with imprecise data. Perhaps the most popular fuzzy DEA model is based on a-cut. One drawback of the a-cut approach is that it cannot include all information about uncertainty. This paper aims to introduce an alternative linear programming model that can include some uncertainty information from the intervals within the a-cut approach. We introduce the concept of "local a-level" to develop a multi-objective linear programming to measure the efficiency of DMUs under uncertainty. An example is given to illustrate the use of this method.

Fitness and novelty in evolutionary art

In this paper the effects of introducing novelty search in evolutionary art are explored. Our algorithm combines fitness and novelty metrics to frame image evolution as a multi-objective optimisation problem, promoting the creation of images that are both suitable and diverse. The method is illustrated by using two evolutionary art engines for the evolution of figurative objects and context free design grammars. The results demonstrate the ability of the algorithm to obtain a larger set of fit images compared to traditional fitness-based evolution, regardless of the engine used.

One Class of Stochastic Local Search Algorithms

Accelerated probabilistic modeling algorithms, presenting stochastic local search (SLS) technique, are considered. General algorithm scheme and specific combinatorial optimization method, using “golden section” rule (GS-method), are given. Convergence rates using Markov chains are received. An overview of current combinatorial optimization techniques is presented.

Reduction Measurements for Calculation in Fuzzy Experiment Scheme

The papers is dedicated to the questions of modeling and basing super-resolution measuring- calculating systems in the context of the conception “device + PC = new possibilities”. By the authors of the article the new mathematical method of solution of the multi-criteria optimization problems was developed. The method is based on physic-mathematical formalism of reduction of fuzzy disfigured measurements. It is shown, that determinative part is played by mathematical properties of physical models of the object, which is measured, surroundings, measuring components of measuring-calculating systems and theirs cooperation as well as the developed mathematical method of processing and interpretation of measurements problem solution.