Optimization methods for the operating room management under uncertainty: stochastic programming vs. decomposition approach

The operating theatres are the engine of the hospitals; proper management of the operating rooms and its staff represents a great challenge for managers and its results impact directly in the budget of the hospital. This work presents a MILP model for the efficient schedule of multiple surgeries in Operating Rooms (ORs) during a working day. This model considers multiple surgeons and ORs and different types of surgeries. Stochastic strategies are also implemented for taking into account the uncertain in surgery durations (pre-incision, incision, post-incision times). In addition, a heuristic-based methods and a MILP decomposition approach is proposed for solving large-scale ORs scheduling problems in computational efficient way. All these computer-aided strategies has been implemented in AIMMS, as an advanced modeling and optimization software, developing a user friendly solution tool for the operating room management under uncertainty.

Multi-agent Architecture for Heterogeneous Reasoning under Uncertainty Combining MSBN and Ontologies in Distributed Network Diagnosis

This article proposes a MAS architecture for network diagnosis under uncertainty. Network diagnosis is divided into two inference processes: hypothesis generation and hypothesis confirmation. The first process is distributed among several agents based on a MSBN, while the second one is carried out by agents using semantic reasoning. A diagnosis ontology has been defined in order to combine both inference processes. To drive the deliberation process, dynamic data about the influence of observations are taken during diagnosis process. In order to achieve quick and reliable diagnoses, this influence is used to choose the best action to perform. This approach has been evaluated in a P2P video streaming scenario. Computational and time improvements are highlight as conclusions.

Supporting decision making under uncertainty: Development of a participatory integrated model for water management in the middle Guadiana river basin.

Following the Integrated Water Resources Management approach, the European Water Framework Directive demands Member States to develop water management plans at the catchment level. Those plans have to integrate the different interests and must be developed with stakeholder participation. To face these requirements, managers need tools to assess the impacts of possible management alternatives on natural and socio-economic systems. These tools should ideally be able to address the complexity and uncertainties of the water system, while serving as a platform for stakeholder participation. The objective of our research was to develop a participatory integrated assessment model, based on the combination of a crop model, an economic model and a participatory Bayesian network, with an application in the middle Guadiana sub-basin, in Spain. The methodology is intended to capture the complexity of water management problems, incorporating the relevant sectors, as well as the relevant scales involved in water management decision making. The integrated model has allowed us testing different management, market and climate change scenarios and assessing the impacts of such scenarios on the natural system (crops), on the socio-economic system (farms) and on the environment (water resources). Finally, this integrated assessment modelling process has allowed stakeholder participation, complying with the main requirements of current European water laws.

Participatory modelling to support decision making in water management under uncertainty: Two comparative case studies in the Guadiana river basin, Spain.

A participatory modelling process has been conducted in two areas of the Guadiana river (the upper and the middle sub-basins), in Spain, with the aim of providing support for decision making in the water management field. The area has a semi-arid climate where irrigated agriculture plays a key role in the economic development of the region and accounts for around 90% of water use. Following the guidelines of the European Water Framework Directive, we promote stakeholder involvement in water management with the aim to achieve an improved understanding of the water system and to encourage the exchange of knowledge and views between stakeholders in order to help building a shared vision of the system. At the same time, the resulting models, which integrate the different sectors and views, provide some insight of the impacts that different management options and possible future scenarios could have. The methodology is based on a Bayesian network combined with an economic model and, in the middle Guadiana sub-basin, with a crop model. The resulting integrated modelling framework is used to simulate possible water policy, market and climate scenarios to find out the impacts of those scenarios on farm income and on the environment. At the end of the modelling process, an evaluation questionnaire was filled by participants in both sub-basins. Results show that this type of processes are found very helpful by stakeholders to improve the system understanding, to understand each others views and to reduce conflict when it exists. In addition, they found the model an extremely useful tool to support management. The graphical interface, the quantitative output and the explicit representation of uncertainty helped stakeholders to better understand the implications of the scenario tested. Finally, the combination of different types of models was also found very useful, as it allowed exploring in detail specific aspects of the water management problems.

Service Capacity Reserve under Uncertainty by Hospital’s ER Analogies: A Practical Model for Car Services

We define a capacity reserve model to dimension passenger car service installations according to the demographic distribution of the area to be serviced by using hospital?s emergency room analogies. Usually, service facilities are designed applying empirical methods, but customers arrive under uncertain conditions not included in the original estimations, and there is a gap between customer?s real demand and the service?s capacity. Our research establishes a valid methodology and covers the absence of recent researches and the lack of statistical techniques implementation, integrating demand uncertainty in a unique model built in stages by implementing ARIMA forecasting, queuing theory, and Monte Carlo simulation to optimize the service capacity and occupancy, minimizing the implicit cost of the capacity that must be reserved to service unexpected customers. Our model has proved to be a useful tool for optimal decision making under uncertainty integrating the prediction of the cost implicit in the reserve capacity to serve unexpected demand and defining a set of new process indicators, such us capacity, occupancy, and cost of capacity reserve never studied before. The new indicators are intended to optimize the service operation. This set of new indicators could be implemented in the information systems used in the passenger car services.

Service capacity reserve under uncertainty by hospital's ER's analogies: a practical model for car services

El objetivo de esta investigación consiste en definir un modelo de reserva de capacidad, por analogías con emergencias hospitalarias, que pueda ser implementado en el sector de servicios. Este está específicamente enfocado a su aplicación en talleres de servicio de automóviles. Nuestra investigación incorpora la incertidumbre de la demanda en un modelo singular diseñado en etapas que agrupa técnicas ARIMA, teoría de colas y simulación Monte Carlo para definir los conceptos de capacidad y ocupación de servicio, que serán utilizados para minimizar el coste implícito de la reserva capacidad necesaria para atender a clientes que carecen de cita previa. Habitualmente, las compañías automovilísticas estiman la capacidad de sus instalaciones de servicio empíricamente, pero los clientes pueden llegar bajo condiciones de incertidumbre que no se tienen en cuenta en dichas estimaciones, por lo que existe una diferencia entre lo que el cliente realmente demanda y la capacidad que ofrece el servicio. Nuestro enfoque define una metodología válida para el sector automovilístico que cubre la ausencia genérica de investigaciones recientes y la habitual falta de aplicación de técnicas estadísticas en el sector. La equivalencia con la gestión de urgencias hospitalarias se ha validado a lo largo de la investigación en la se definen nuevos indicadores de proceso (KPIs) Tal y como hacen los hospitales, aplicamos modelos estocásticos para dimensionar las instalaciones de servicio de acuerdo con la distribución demográfica del área de influencia. El modelo final propuesto integra la predicción del coste implícito en la reserva de capacidad para atender la demanda no prevista. Asimismo, se ha desarrollado un código en Matlab que puede integrarse como un módulo adicional a los sistemas de información (DMS) que se usan actualmente en el sector, con el fin de emplear los nuevos indicadores de proceso definidos en el modelo. Los resultados principales del modelo son nuevos indicadores de servicio, tales como la capacidad, ocupación y coste de reserva de capacidad, que nunca antes han sido objeto de estudio en la industria automovilística, y que están orientados a gestionar la operativa del servicio. ABSTRACT Our aim is to define a Capacity Reserve model to be implemented in the service sector by hospital's emergency room (ER) analogies, with a practical approach to passenger car services. A stochastic model has been implemented using R and a Monte Carlo simulation code written in Matlab and has proved a very useful tool for optimal decision making under uncertainty. The research integrates demand uncertainty in a unique model which is built in stages by implementing ARIMA forecasting, Queuing Theory and a Monte Carlo simulation to define the concepts of service capacity and occupancy, minimizing the implicit cost of the capacity that must be reserved to service unexpected customers. Usually, passenger car companies estimate their service facilities capacity using empirical methods, but customers arrive under uncertain conditions not included in the estimations. Thus, there is a gap between customer’s real demand and the dealer’s capacity. This research sets a valid methodology for the passenger car industry to cover the generic absence of recent researches and the generic lack of statistical techniques implementation. The hospital’s emergency room (ER) equalization has been confirmed to be valid for the passenger car industry and new process indicators have been defined to support the study. As hospitals do, we aim to apply stochastic models to dimension installations according to the demographic distribution of the area to be serviced. The proposed model integrates the prediction of the cost implicit in the reserve capacity to serve unexpected demand. The Matlab code could be implemented as part of the existing information technology systems (ITs) to support the existing service management tools, creating a set of new process indicators. Main model outputs are new indicators, such us Capacity, Occupancy and Cost of Capacity Reserve, never studied in the passenger car service industry before, and intended to manage the service operation.

Modelling and forecasting fossil fuels, CO2 and electricity prices and their volatilities

In the current uncertain context that affects both the world economy and the energy sector, with the rapid increase in the prices of oil and gas and the very unstable political situation that affects some of the largest raw materials’ producers, there is a need for developing efficient and powerful quantitative tools that allow to model and forecast fossil fuel prices, CO2 emission allowances prices as well as electricity prices. This will improve decision making for all the agents involved in energy issues. Although there are papers focused on modelling fossil fuel prices, CO2 prices and electricity prices, the literature is scarce on attempts to consider all of them together. This paper focuses on both building a multivariate model for the aforementioned prices and comparing its results with those of univariate ones, in terms of prediction accuracy (univariate and multivariate models are compared for a large span of days, all in the first 4 months in 2011) as well as extracting common features in the volatilities of the prices of all these relevant magnitudes. The common features in volatility are extracted by means of a conditionally heteroskedastic dynamic factor model which allows to solve the curse of dimensionality problem that commonly arises when estimating multivariate GARCH models. Additionally, the common volatility factors obtained are useful for improving the forecasting intervals and have a nice economical interpretation. Besides, the results obtained and methodology proposed can be useful as a starting point for risk management or portfolio optimization under uncertainty in the current context of energy markets.

Application of self-organizing techniques for the distribution of heterogeneous multi-tasks in multi-robot systems

This paper focuses on the general problem of coordinating of multi-robot systems, more specifically, it addresses the self-election of heterogeneous and specialized tasks by autonomous robots. In this regard, it has proposed experimenting with two different techniques based chiefly on selforganization and emergence biologically inspired, by applying response threshold models as well as ant colony optimization. Under this approach it can speak of multi-tasks selection instead of multi-tasks allocation, that means, as the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. It has evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

B2DI a bayesian BDI agent model with causal belief updating based on MSBN

In this paper, we introduce B2DI model that extends BDI model to perform Bayesian inference under uncertainty. For scalability and flexibility purposes, Multiply Sectioned Bayesian Network (MSBN) technology has been selected and adapted to BDI agent reasoning. A belief update mechanism has been defined for agents, whose belief models are connected by public shared beliefs, and the certainty of these beliefs is updated based on MSBN. The classical BDI agent architecture has been extended in order to manage uncertainty using Bayesian reasoning. The resulting extended model, so-called B2DI, proposes a new control loop. The proposed B2DI model has been evaluated in a network fault diagnosis scenario. The evaluation has compared this model with two previously developed agent models. The evaluation has been carried out with a real testbed diagnosis scenario using JADEX. As a result, the proposed model exhibits significant improvements in the cost and time required to carry out a reliable diagnosis.

Diseño basado en técnicas de fiabilidad del tratamiento de mejora del terreno mediante columnas de grava

El proyecto geotécnico de columnas de grava tiene todas las incertidumbres asociadas a un proyecto geotécnico y además hay que considerar las incertidumbres inherentes a la compleja interacción entre el terreno y la columna, la puesta en obra de los materiales y el producto final conseguido. Este hecho es común a otros tratamientos del terreno cuyo objetivo sea, en general, la mejora “profunda”. Como los métodos de fiabilidad (v.gr., FORM, SORM, Monte Carlo, Simulación Direccional) dan respuesta a la incertidumbre de forma mucho más consistente y racional que el coeficiente de seguridad tradicional, ha surgido un interés reciente en la aplicación de técnicas de fiabilidad a la ingeniería geotécnica. Si bien la aplicación concreta al proyecto de técnicas de mejora del terreno no es tan extensa. En esta Tesis se han aplicado las técnicas de fiabilidad a algunos aspectos del proyecto de columnas de grava (estimación de asientos, tiempos de consolidación y aumento de la capacidad portante) con el objetivo de efectuar un análisis racional del proceso de diseño, considerando los efectos que tienen la incertidumbre y la variabilidad en la seguridad del proyecto, es decir, en la probabilidad de fallo. Para alcanzar este objetivo se ha utilizado un método analítico avanzado debido a Castro y Sagaseta (2009), que mejora notablemente la predicción de las variables involucradas en el diseño del tratamiento y su evolución temporal (consolidación). Se ha estudiado el problema del asiento (valor y tiempo de consolidación) en el contexto de la incertidumbre, analizando dos modos de fallo: i) el primer modo representa la situación en la que es posible finalizar la consolidación primaria, parcial o totalmente, del terreno mejorado antes de la ejecución de la estructura final, bien sea por un precarga o porque la carga se pueda aplicar gradualmente sin afectar a la estructura o instalación; y ii) por otra parte, el segundo modo de fallo implica que el terreno mejorado se carga desde el instante inicial con la estructura definitiva o instalación y se comprueba que el asiento final (transcurrida la consolidación primaria) sea lo suficientemente pequeño para que pueda considerarse admisible. Para trabajar con valores realistas de los parámetros geotécnicos, los datos se han obtenido de un terreno real mejorado con columnas de grava, consiguiendo, de esta forma, un análisis de fiabilidad más riguroso. La conclusión más importante, obtenida del análisis de este caso particular, es la necesidad de precargar el terreno mejorado con columnas de grava para conseguir que el asiento ocurra de forma anticipada antes de la aplicación de la carga correspondiente a la estructura definitiva. De otra forma la probabilidad de fallo es muy alta, incluso cuando el margen de seguridad determinista pudiera ser suficiente. En lo que respecta a la capacidad portante de las columnas, existen un buen número de métodos de cálculo y de ensayos de carga (tanto de campo como de laboratorio) que dan predicciones dispares del valor de la capacidad última de las columnas de grava. En las mallas indefinidas de columnas, los resultados del análisis de fiabilidad han confirmado las consideraciones teóricas y experimentales existentes relativas a que no se produce fallo por estabilidad, obteniéndose una probabilidad de fallo prácticamente nula para este modo de fallo. Sin embargo, cuando se analiza, en el contexto de la incertidumbre, la capacidad portante de pequeños grupos de columnas bajo zapatas se ha obtenido, para un caso con unos parámetros geotécnicos típicos, que la probabilidad de fallo es bastante alta, por encima de los umbrales normalmente admitidos para Estados Límite Últimos. Por último, el trabajo de recopilación sobre los métodos de cálculo y de ensayos de carga sobre la columna aislada ha permitido generar una base de datos suficientemente amplia como para abordar una actualización bayesiana de los métodos de cálculo de la columna de grava aislada. El marco bayesiano de actualización ha resultado de utilidad en la mejora de las predicciones de la capacidad última de carga de la columna, permitiendo “actualizar” los parámetros del modelo de cálculo a medida que se dispongan de ensayos de carga adicionales para un proyecto específico. Constituye una herramienta valiosa para la toma de decisiones en condiciones de incertidumbre ya que permite comparar el coste de los ensayos adicionales con el coste de una posible rotura y , en consecuencia, decidir si es procedente efectuar dichos ensayos. The geotechnical design of stone columns has all the uncertainties associated with a geotechnical project and those inherent to the complex interaction between the soil and the column, the installation of the materials and the characteristics of the final (as built) column must be considered. This is common to other soil treatments aimed, in general, to “deep” soil improvement. Since reliability methods (eg, FORM, SORM, Monte Carlo, Directional Simulation) deals with uncertainty in a much more consistent and rational way than the traditional safety factor, recent interest has arisen in the application of reliability techniques to geotechnical engineering. But the specific application of these techniques to soil improvement projects is not as extensive. In this thesis reliability techniques have been applied to some aspects of stone columns design (estimated settlements, consolidation times and increased bearing capacity) to make a rational analysis of the design process, considering the effects of uncertainty and variability on the safety of the project, i.e., on the probability of failure. To achieve this goal an advanced analytical method due to Castro and Sagaseta (2009), that significantly improves the prediction of the variables involved in the design of treatment and its temporal evolution (consolidation), has been employed. This thesis studies the problem of stone column settlement (amount and speed) in the context of uncertainty, analyzing two failure modes: i) the first mode represents the situation in which it is possible to cause primary consolidation, partial or total, of the improved ground prior to implementation of the final structure, either by a pre-load or because the load can be applied gradually or programmed without affecting the structure or installation; and ii) on the other hand, the second mode implies that the improved ground is loaded from the initial instant with the final structure or installation, expecting that the final settlement (elapsed primary consolidation) is small enough to be allowable. To work with realistic values of geotechnical parameters, data were obtained from a real soil improved with stone columns, hence producing a more rigorous reliability analysis. The most important conclusion obtained from the analysis of this particular case is the need to preload the stone columns-improved soil to make the settlement to occur before the application of the load corresponding to the final structure. Otherwise the probability of failure is very high, even when the deterministic safety margin would be sufficient. With respect to the bearing capacity of the columns, there are numerous methods of calculation and load tests (both for the field and the laboratory) giving different predictions of the ultimate capacity of stone columns. For indefinite columns grids, the results of reliability analysis confirmed the existing theoretical and experimental considerations that no failure occurs due to the stability failure mode, therefore resulting in a negligible probability of failure. However, when analyzed in the context of uncertainty (for a case with typical geotechnical parameters), results show that the probability of failure due to the bearing capacity failure mode of a group of columns is quite high, above thresholds usually admitted for Ultimate Limit States. Finally, the review of calculation methods and load tests results for isolated columns, has generated a large enough database, that allowed a subsequent Bayesian updating of the methods for calculating the bearing capacity of isolated stone columns. The Bayesian updating framework has been useful to improve the predictions of the ultimate load capacity of the column, allowing to "update" the parameters of the calculation model as additional load tests become available for a specific project. Moreover, it is a valuable tool for decision making under uncertainty since it is possible to compare the cost of further testing to the cost of a possible failure and therefore to decide whether it is appropriate to perform such tests.

Water option contracts for reducing water supply risks: an application to the Tagus-Segura Transfer

El agua es un recurso cada vez más escaso y valioso. Por ello, los recursos hídricos disponibles deben asignarse de una forma eficiente entre los diferentes usos. El cambio climático aumentará la frecuencia y severidad de los eventos extremos, y podría incrementar la demanda de agua de los cultivos. El empleo de mecanismos flexibles de asignación de agua puede ser imprescindible para hacer frente a este aumento en la variabilidad del balance hídrico y para asegurar que los riesgos de suministro, y no solo los recursos, son compartidos de manera eficiente entre los usuarios. Los mercados de agua permiten la reasignación de los recursos hídricos, favoreciendo su transferencia desde los usos de menor a los de mayor valor. Diferentes tipos de mercados de agua se han establecido en diferentes partes del mundo, ayudando a los participantes a afrontar los problemas de escasez de agua en esas zonas. En España, los intercambios de agua están permitidos desde 1999, aunque la participación de los usuarios en el mercado ha sido limitada. Hay varios aspectos de los mercados de agua en España que deben mejorarse. Esta tesis, además de proponer una serie de cambios en el marco regulatorio, propone la introducción de contratos de opción de agua como una posible mejora. La principal ventaja de este tipo de contratos es la estabilidad legal e institucional que éstos proporcionan tanto a compradores como vendedores. Para apoyar esta propuesta, se han llevado a cabo diferentes análisis que muestran el potencial de los contratos de opción como herramienta de reducción del riesgo asociado a una oferta de agua inestable. La Cuenca del Segura (Sureste de España), la Cuenca del Tajo y el Acueducto Tajo- Segura han sido seleccionados como casos de estudio. Tres análisis distintos aplicados a dicha región se presentan en esta tesis: a) una evaluación de los contratos de opción como mecanismo para reducir los riesgos de disponibilidad de agua sufridos por los regantes en la Cuenca del Segura; b) un marco teórico para analizar las preferencias de los regantes por diferentes mecanismos de gestión del riesgo de disponibilidad de agua, su disposición a pagar por ellos y los precios aproximados de estos instrumentos (seguro de sequía y contratos de opción de agua); y c) una evaluación del papel de los contratos de opción en las decisiones de aprovisionamiento de agua de una comunidad de regantes ante una oferta de agua incierta. Los resultados muestran el potencial de reducción del riesgo de los contratos de opción para regantes en España, pero pueden ser extrapolados a otros sectores o regiones. Las principales conclusiones de esta tesis son: a) la agricultura será uno de los sectores más afectados por el cambio climático. Si los precios del agua aumentan, la rentabilidad de los cultivos puede caer hasta niveles negativos, lo que podría dar lugar al abandono de cultivos de regadío en algunas zonas de España. Las políticas de cambio climático y de agua deben estar estrechamente coordinadas para asegurar un uso de agua eficiente y la rentabilidad de la agricultura; b) aunque los mercados de agua han ayudado a algunos usuarios a afrontar problemas de disponibilidad del recurso en momentos de escasez, hay varios aspectos que deben mejorarse; c) es necesario desarrollar mercados de agua más flexibles y estables para garantizar una asignación eficiente de los recursos entre los usuarios de agua; d) los resultados muestran los beneficios derivados del establecimiento de un contrato de opción entre usuarios de agua del Tajo y del Segura para reducir el riesgo de disponibilidad de agua en la cuenca receptora; e) la disposición a pagar de los regantes por un contrato de opción de agua o un seguro de sequía hidrológica, que representa el valor que tienen estos mecanismos para aquellos usuarios de agua que se enfrentan a riesgos relacionados con la disponibilidad del recurso, es consistente con los resultados obtenidos en estudios previos y superior al precio de mercado de estos instrumentos, lo que favorece la viabilidad de estos mecanismos de gestión del riesgo ; y f) los contratos de opción podrían ayudar a optimizar las decisiones de aprovisionamiento de agua bajo incertidumbre, proporcionando más estabilidad y flexibilidad que los mercados temporales de agua. ABSTRACT Water is becoming increasingly scarce and valuable. Thus, existing water resources need to be efficiently allocated among users. Climate change is expected to increase the frequency and severity of extreme events, and it may also increase irrigated crops' water demand. The implementation of flexible allocation mechanisms could be essential to cope with this increased variability of the water balance and ensure that supply risks, and not only water resources, are also efficiently shared and managed. Water markets allow for the reallocation of water resources from low to high value uses. Different water trading mechanisms have been created in different parts of the world and have helped users to alleviate water scarcity problems in those areas. In Spain, water trading is allowed since 1999, although market activity has been limited. There are several issues in the Spanish water market that should be improved. This thesis, besides proposing several changes in the legislative framework, proposes the introduction of water option contracts as a potential improvement. The main advantage for both buyer and seller derived from an option contract is the institutional and legal stability it provides. To support this proposal, different analyses have been carried out that show the potential of option contracts as a risk reduction tool to manage water supply instability. The Segura Basin (Southeast Spain), the Tagus Basin and the Tagus-Segura inter-basin Transfer have been selected as the case study. Three different analyses applied to this region are presented in this thesis: a) an evaluation of option contracts as a mechanisms to reduce water supply availability risks in the Segura Basin; b) a theoretical framework for analyzing farmer’s preferences for different water supply risk management tools and farmers’ willingness to pay for them, together with the assessment of the prices of these mechanisms (drought insurance and water option contracts); and c) an evaluation of the role of option contracts in water procurement decisions under uncertainty. Results show the risk-reduction potential of option contracts for the agricultural sector in Spain, but these results can be extrapolated to other sectors or regions. The main conclusions of the thesis are: a) agriculture would be one of the most affected sectors by climate change. With higher water tariffs, crop’s profitability can drop to negative levels, which may result in the abandoning of the crop in many areas. Climate change and water policies must be closely coordinated to ensure efficient water use and crops’ profitability; b) although Spanish water markets have alleviated water availability problems for some users during water scarcity periods, there are several issues that should be improved; c) more flexible and stable water market mechanisms are needed to allocate water resources and water supply risks among competing users; d) results show the benefits derived from the establishment of an inter-basin option contract between water users in the Tagus and the Segura basins for reducing water supply availability risks in the recipient area; e) irrigators’ willingness to pay for option contracts or drought insurance, that represent the value that this kind of trading mechanisms has for water users facing water supply reliability problems, are consistent with results obtained in previous works and higher than the prices of this risk management tools, which shows the feasibility of these mechanisms; and f) option contracts would help to optimize water procurement decisions under uncertainty, providing more flexibility and stability than the spot market.

Aproximaciones del conjunto eficiente en decisión multicriterio

El conjunto eficiente en la Teoría de la Decisión Multicriterio juega un papel fundamental en los procesos de solución ya que es en este conjunto donde el decisor debe hacer su elección más preferida. Sin embargo, la generación de tal conjunto puede ser difícil, especialmente en problemas continuos y/o no lineales. El primer capítulo de esta memoria, es introductorio a la Decisión Multicriterio y en él se exponen aquellos conceptos y herramientas que se van a utilizar en desarrollos posteriores. El segundo capítulo estudia los problemas de Toma de Decisiones en ambiente de certidumbre. La herramienta básica y punto de partida es la función de valor vectorial que refleja imprecisión sobre las preferencias del decisor. Se propone una caracterización del conjunto de valor eficiente y diferentes aproximaciones con sus propiedades de encaje y convergencia. Varios algoritmos interactivos de solución complementan los desarrollos teóricos. El tercer capítulo está dedicado al caso de ambiente de incertidumbre. Tiene un desarrollo parcialmente paralelo al anterior y utiliza la función de utilidad vectorial como herramienta de modelización de preferencias del decisor. A partir de la consideración de las distribuciones simples se introduce la eficiencia en utilidad, su caracterización y aproximaciones, que posteriormente se extienden a los casos de distribuciones discretas y continuas. En el cuarto capítulo se estudia el problema en ambiente difuso, aunque de manera introductoria. Concluimos sugiriendo distintos problemas abiertos.---ABSTRACT---The efficient set of a Multicriteria Decicion-Making Problem plays a fundamental role in the solution process since the Decisión Maker's preferred choice should be in this set. However, the computation of that set may be difficult, specially in continuous and/or nonlinear problems. Chapter one introduces Multicriteria Decision-Making. We review basic concepts and tools for later developments. Chapter two studies Decision-Making problems under certainty. The basic tool is the vector valué function, which represents imprecisión in the DM's preferences. We propose a characterization of the valué efficient set and different approximations with nesting and convergence properties. Several interactive algorithms complement the theoretical results. We devote Chapter three to problems under uncertainty. The development is parallel to the former and uses vector utility functions to model the DM's preferences. We introduce utility efficiency for simple distributions, its characterization and some approximations, which we partially extend to discrete and continuous classes of distributions. Chapter four studies the problem under fuzziness, at an exploratory level. We conclude with several open problems.

Adverse aerodynamics effects of a high speed train under the influence of cross winds, analysis and optimization of wind fence

The research work that here is summarized, it is classed on the area of dynamics and measures of railway safety, specifically in the study of the influence of the cross wind on the high-speed trains as well as the study of new mitigation measures like wind breaking structures or wind fences, with optimized shapes. The work has been developed in the Research Center in Rail Technology (CITEF), and supported by the Universidad Politécnica de Madrid, Spain.

A method to incorporate the effect of taxonomic uncertainty on multivariate analyses of ecological data

Researchers in ecology commonly use multivariate analyses (e.g. redundancy analysis, canonical correspondence analysis, Mantel correlation, multivariate analysis of variance) to interpret patterns in biological data and relate these patterns to environmental predictors. There has been, however, little recognition of the errors associated with biological data and the influence that these may have on predictions derived from ecological hypotheses. We present a permutational method that assesses the effects of taxonomic uncertainty on the multivariate analyses typically used in the analysis of ecological data. The procedure is based on iterative randomizations that randomly re-assign non identified species in each site to any of the other species found in the remaining sites. After each re-assignment of species identities, the multivariate method at stake is run and a parameter of interest is calculated. Consequently, one can estimate a range of plausible values for the parameter of interest under different scenarios of re-assigned species identities. We demonstrate the use of our approach in the calculation of two parameters with an example involving tropical tree species from western Amazonia: 1) the Mantel correlation between compositional similarity and environmental distances between pairs of sites, and; 2) the variance explained by environmental predictors in redundancy analysis (RDA). We also investigated the effects of increasing taxonomic uncertainty (i.e. number of unidentified species), and the taxonomic resolution at which morphospecies are determined (genus-resolution, family-resolution, or fully undetermined species) on the uncertainty range of these parameters. To achieve this, we performed simulations on a tree dataset from southern Mexico by randomly selecting a portion of the species contained in the dataset and classifying them as unidentified at each level of decreasing taxonomic resolution. An analysis of covariance showed that both taxonomic uncertainty and resolution significantly influence the uncertainty range of the resulting parameters. Increasing taxonomic uncertainty expands our uncertainty of the parameters estimated both in the Mantel test and RDA. The effects of increasing taxonomic resolution, however, are not as evident. The method presented in this study improves the traditional approaches to study compositional change in ecological communities by accounting for some of the uncertainty inherent to biological data. We hope that this approach can be routinely used to estimate any parameter of interest obtained from compositional data tables when faced with taxonomic uncertainty.

A Methodological model to assist the optimization and risk management of mining investment decisions

Identifying, quantifying, and minimizing technical risks associated with investment decisions is a key challenge for mineral industry decision makers and investors. However, risk analysis in most bankable mine feasibility studies are based on the stochastic modelling of project “Net Present Value” (NPV)which, in most cases, fails to provide decision makers with a truly comprehensive analysis of risks associated with technical and management uncertainty and, as a result, are of little use for risk management and project optimization. This paper presents a value-chain risk management approach where project risk is evaluated for each step of the project lifecycle, from exploration to mine closure, and risk management is performed as a part of a stepwise value-added optimization process.