Robustness and Recoverability in Transport Logistics

Abstract Transport is the foundation of any economy: it boosts economic growth, creates wealth, enhances trade, geographical accessibility and the mobility of people. Transport is also a key ingredient for a high quality of life, making places accessible and bringing people together. The future prosperity of our world will depend on the ability of all of its regions to remain fully and competitively integrated in the world economy. Efficient transport is vital in making this happen. Operations research can help in efficiently planning the design and operating transport systems. Planning and operational processes are fields that are rich in combinatorial optimization problems. These problems can be analyzed and solved through the application of mathematical models and optimization techniques, which may lead to an improvement in the performance of the transport system, as well as to a reduction in the time required for solving these problems. The latter aspect is important, because it increases the flexibility of the system: the system can adapt in a faster way to changes in the environment (i.e.: weather conditions, crew illness, failures, etc.). These disturbing changes (called disruptions) often enforce the schedule to be adapted. The direct consequences are delays and cancellations, implying many schedule adjustments and huge costs. Consequently, robust schedules and recovery plans must be developed in order to fight against disruptions. This dissertation makes contributions to two different fields: rail and air applications. Robust planning and recovery methods are presented. In the field of railway transport we develop several mathematical models which answer to RENFE’s (the major railway operator in Spain) needs: 1. We study the rolling stock assignment problem: here, we introduce some robust aspects in order to ameliorate some operations which are likely to fail. Once the rolling stock assignment is known, we propose a robust routing model which aims at identifying the train units’ sequences while minimizing the expected delays and human resources needed to perform the sequences. 2. It is widely accepted that the sequential solving approach produces solutions that are not global optima. Therefore, we develop an integrated and robust model to determine the train schedule and rolling stock assignment. We also propose an integrated model to study the rolling stock circulations. Circulations are determined by the rolling stock assignment and routing of the train units. 3. Although our aim is to develop robust plans, disruptions will be likely to occur and recovery methods will be needed. Therefore, we propose a recovery method which aims to recover the train schedule and rolling stock assignment in an integrated fashion all while considering the passenger demand. In the field of air transport we develop several mathematical models which answer to IBERIA’s (the major airline in Spain) needs: 1. We look at the airline-scheduling problem and develop an integrated approach that optimizes schedule design, fleet assignment and passenger use so as to reduce costs and create fewer incompatibilities between decisions. Robust itineraries are created to ameliorate misconnected passengers. 2. Air transport operators are continuously facing competition from other air operators and different modes of transport (e.g., High Speed Rail). Consequently, airline profitability is critically influenced by the airline’s ability to estimate passenger demands and construct profitable flight schedules. We consider multi-modal competition including airline and rail, and develop a new approach that estimates the demand associated with a given schedule; and generates airline schedules and fleet assignments using an integrated schedule design and fleet assignment optimization model that captures the impacts of schedule decisions on passenger demand.

A fuzzy approach to risk analysis in information systems

Assets are interrelated in risk analysis methodologies for information systems promoted by international standards. This means that an attack on one asset can be propagated through the network and threaten an organization's most valuable assets. It is necessary to valuate all assets, the direct and indirect asset dependencies, as well as the probability of threats and the resulting asset degradation. These methodologies do not, however, consider uncertain valuations and use precise values on different scales, usually percentages. Linguistic terms are used by the experts to represent assets values, dependencies and frequency and asset degradation associated with possible threats. Computations are based on the trapezoidal fuzzy numbers associated with these linguistic terms.

A first approach to the optimization of Bogotá's TransMilenio BRT system

Bus rapid transit (BRT) systems are massive transport systems with medium/high capacity, high quality service and low infrastructure and operating costs. TransMilenio is Bogotá's most important mass transportation system and one of the biggest BRT systems in the world, although it only has completed its third construction phase out of a total of eight. In this paper we review the proposals in the literature to optimize BRT system operation, with a special emphasis on TransMilenio, and propose a mathematical model that adapts elements of the above proposals and incorporates novel elements accounting for the features of TransMilenio system.

Data Mining with Enhanced Neural Networks-CMMSE

Abstract This paper presents a new method to extract knowledge from existing data sets, that is, to extract symbolic rules using the weights of an Artificial Neural Network. The method has been applied to a neural network with special architecture named Enhanced Neural Network (ENN). This architecture improves the results that have been obtained with multilayer perceptron (MLP). The relationship among the knowledge stored in the weights, the performance of the network and the new implemented algorithm to acquire rules from the weights is explained. The method itself gives a model to follow in the knowledge acquisition with ENN.

Active Learning and Dynamic Pricing Policies

In this paper, we address the problem of dynamic pricing to optimize the revenue coming from the sales of a limited inventory in a finite time-horizon. A priori, the demand is assumed to be unknown. The seller must learn on the fly. We first deal with the simplest case, involving only one class of product for sale. Furthermore the general situation is considered with a finite number of product classes for sale. In particular, a case in point is the sale of tickets for events related to culture and leisure; in this case, typically the tickets are sold months before the event, thus, uncertainty over actual demand levels is a very a common occurrence. We propose a heuristic strategy of adaptive dynamic pricing, based on experience gained from the past, taking into account, for each time period, the available inventory, the time remaining to reach the horizon, and the profit made in previous periods. In the computational simulations performed, the demand is updated dynamically based on the prices being offered, as well as on the remaining time and inventory. The simulations show a significant profit over the fixed-price strategy, confirming the practical usefulness of the proposed strategy. We develop a tool allowing us to test different dynamic pricing strategies designed to fit market conditions and seller s objectives, which will facilitate data analysis and decision-making in the face of the problem of dynamic pricing.

Geometric Study of the Weak Equilibrium in a Weighted Case for a Two-Dimensional Competition Game

In this work, an improvement of the results presented by [1] Abellanas et al. (Weak Equilibrium in a Spatial Model. International Journal of Game Theory, 40(3), 449-459) is discussed. Concretely, this paper investigates an abstract game of competition between two players that want to earn the maximum number of points from a finite set of points in the plane. It is assumed that the distribution of these points is not uniform, so an appropriate weight to each position is assigned. A definition of equilibrium which is weaker than the classical one is included in order to avoid the uniqueness of the equilibrium position typical of the Nash equilibrium in these kinds of games. The existence of this approximated equilibrium in the game is analyzed by means of computational geometry techniques.

Discrete Multi-Criteria Methods for lands use and conservation planning on La Colacha in Arroyos Menores (Río Cuarto, Province of Córdoba, Argentina)

The study area is La Colacha sub-basins from Arroyos Menores basins, natural areas at West and South of Río Cuarto in Province of Córdoba of Argentina, fertile with loess soils and monsoon temperate climate, but with soil erosions including regressive gullies that degrade them progressively. Cultivated gently since some hundred sixty years, coordinated action planning became necessary to conserve lands while keeping good agro-production. The authors had improved data on soils and on hydrology for the study area, evaluated systems of soil uses and actions to be recommended and applied Decision Support Systems (DSS) tools for that, and were conducted to use discrete multi-criteria models (MCDM) for the more global views about soil conservation and hydraulic management actions and about main types of use of soils. For that they used weighted PROMETHEE, ELECTRE, and AHP methods with a system of criteria grouped as environmental, economic and social, and criteria from their data on effects of criteria. The alternatives resulting offer indication for planning depending somehow on sub basins and on selections of weights, but actions for conservation of soils and water management measures are recommended to conserve the basins conditions, actually sensibly degrading, mainly keeping actual uses of the lands.

Coordination mechanisms and software in industrial networks - a literature review

This paper groups recent supply chain management research focused on organizational design and its software support. The classification encompasses criteria related to research methodology and content. Empirical studies from management science focus on network types and organizational fit. Novel planning algorithms and innovative coordination schemes are developed mostly in the field of operations research in order to propose new software features. Operations and production management realize cost-benefit analysis of IT software implementations. The success of software solutions for network coordination depends strongly on the fit of three dimensions: network configuration, coordination scheme and software functionality. This paper concludes with proposals for future research on unaddressed issues within and among the identified research streams.

An Ant Colony System adaptation to deal with accessibility issues after a disaster

One of the main problems relief teams face after a natural or man-made disaster is how to plan rural road repair work tasks to take maximum advantage of the limited available financial and human resources. Previous research focused on speeding up repair work or on selecting the location of health centers to minimize transport times for injured citizens. In spite of the good results, this research does not take into account another key factor: survivor accessibility to resources. In this paper we account for the accessibility issue, that is, we maximize the number of survivors that reach the nearest regional center (cities where economic and social activity is concentrated) in a minimum time by planning which rural roads should be repaired given the available financial and human resources. This is a combinatorial problem since the number of connections between cities and regional centers grows exponentially with the problem size, and exact methods are no good for achieving an optimum solution. In order to solve the problem we propose using an Ant Colony System adaptation, which is based on ants? foraging behavior. Ants stochastically build minimal paths to regional centers and decide if damaged roads are repaired on the basis of pheromone levels, accessibility heuristic information and the available budget. The proposed algorithm is illustrated by means of an example regarding the 2010 Haiti earthquake, and its performance is compared with another metaheuristic, GRASP.

A Fuzzy approach based on dynamic programming and metaheuristics for selecting safeguards for risk management for information systems

In this paper we focus on the selection of safeguards in a fuzzy risk analysis and management methodology for information systems (IS). Assets are connected by dependency relationships, and a failure of one asset may affect other assets. After computing impact and risk indicators associated with previously identified threats, we identify and apply safeguards to reduce risks in the IS by minimizing the transmission probabilities of failures throughout the asset network. However, as safeguards have associated costs, the aim is to select the safeguards that minimize costs while keeping the risk within acceptable levels. To do this, we propose a dynamic programming-based method that incorporates simulated annealing to tackle optimizations problems.

Veto values in Group Decision Making within MAUT: aggregating complete rankings derived from dominance intensity measures

We consider a groupdecision-making problem within multi-attribute utility theory, in which the relative importance of decisionmakers (DMs) is known and their preferences are represented by means of an additive function. We allow DMs to provide veto values for the attribute under consideration and build veto and adjust functions that are incorporated into the additive model. Veto functions check whether alternative performances are within the respective veto intervals, making the overall utility of the alternative equal to 0, where as adjust functions reduce the utilty of the alternative performance to match the preferences of other DMs. Dominance measuring methods are used to account for imprecise information in the decision-making scenario and to derive a ranking of alternatives for each DM. Specifically, ordinal information about the relative importance of criteria is provided by each DM. Finally, an extension of Kemeny's method is used to aggregate the alternative rankings from the DMs accounting for the irrelative importance.

Evaluation of configurations of supply networks supported by it systems

Los sistemas transaccionales tales como los programas informáticos para la planificación de recursos empresariales (ERP software) se han implementado ampliamente mientras que los sistemas analíticos para la gestión de la cadena de suministro (SCM software) no han tenido el éxito deseado por la industria de tecnología de información (TI). Aunque se documentan beneficios importantes derivados de las implantaciones de SCM software, las empresas industriales son reacias a invertir en este tipo de sistemas. Por una parte esto es debido a la falta de métodos que son capaces de detectar los beneficios por emplear esos sistemas, y por otra parte porque el coste asociado no está identificado, detallado y cuantificado suficientemente. Los esquemas de coordinación basados únicamente en sistemas ERP son alternativas válidas en la práctica industrial siempre que la relación coste-beneficio esta favorable. Por lo tanto, la evaluación de formas organizativas teniendo en cuenta explícitamente el coste debido a procesos administrativos, en particular por ciclos iterativos, es de gran interés para la toma de decisiones en el ámbito de inversiones en TI. Con el fin de cerrar la brecha, el propósito de esta investigación es proporcionar métodos de evaluación que permitan la comparación de diferentes formas de organización y niveles de soporte por sistemas informáticos. La tesis proporciona una amplia introducción, analizando los retos a los que se enfrenta la industria. Concluye con las necesidades de la industria de SCM software: unas herramientas que facilitan la evaluación integral de diferentes propuestas de organización. A continuación, la terminología clave se detalla centrándose en la teoría de la organización, las peculiaridades de inversión en TI y la tipología de software de gestión de la cadena de suministro. La revisión de la literatura clasifica las contribuciones recientes sobre la gestión de la cadena de suministro, tratando ambos conceptos, el diseño de la organización y su soporte por las TI. La clasificación incluye criterios relacionados con la metodología de la investigación y su contenido. Los estudios empíricos en el ámbito de la administración de empresas se centran en tipologías de redes industriales. Nuevos algoritmos de planificación y esquemas de coordinación innovadoras se desarrollan principalmente en el campo de la investigación de operaciones con el fin de proponer nuevas funciones de software. Artículos procedentes del área de la gestión de la producción se centran en el análisis de coste y beneficio de las implantaciones de sistemas. La revisión de la literatura revela que el éxito de las TI para la coordinación de redes industriales depende en gran medida de características de tres dimensiones: la configuración de la red industrial, los esquemas de coordinación y las funcionalidades del software. La literatura disponible está enfocada sobre todo en los beneficios de las implantaciones de SCM software. Sin embargo, la coordinación de la cadena de suministro, basándose en el sistema ERP, sigue siendo la práctica industrial generalizada, pero el coste de coordinación asociado no ha sido abordado por los investigadores. Los fundamentos de diseño organizativo eficiente se explican en detalle en la medida necesaria para la comprensión de la síntesis de las diferentes formas de organización. Se han generado varios esquemas de coordinación variando los siguientes parámetros de diseño: la estructura organizativa, los mecanismos de coordinación y el soporte por TI. Las diferentes propuestas de organización desarrolladas son evaluadas por un método heurístico y otro basado en la simulación por eventos discretos. Para ambos métodos, se tienen en cuenta los principios de la teoría de la organización. La falta de rendimiento empresarial se debe a las dependencias entre actividades que no se gestionan adecuadamente. Dentro del método heurístico, se clasifican las dependencias y se mide su intensidad basándose en factores contextuales. A continuación, se valora la idoneidad de cada elemento de diseño organizativo para cada dependencia específica. Por último, cada forma de organización se evalúa basándose en la contribución de los elementos de diseño tanto al beneficio como al coste. El beneficio de coordinación se refiere a la mejora en el rendimiento logístico - este concepto es el objeto central en la mayoría de modelos de evaluación de la gestión de la cadena de suministro. Por el contrario, el coste de coordinación que se debe incurrir para lograr beneficios no se suele considerar en detalle. Procesos iterativos son costosos si se ejecutan manualmente. Este es el caso cuando SCM software no está implementada y el sistema ERP es el único instrumento de coordinación disponible. El modelo heurístico proporciona un procedimiento simplificado para la clasificación sistemática de las dependencias, la cuantificación de los factores de influencia y la identificación de configuraciones que indican el uso de formas organizativas y de soporte de TI más o menos complejas. La simulación de eventos discretos se aplica en el segundo modelo de evaluación utilizando el paquete de software ‘Plant Simulation’. Con respecto al rendimiento logístico, por un lado se mide el coste de fabricación, de inventario y de transporte y las penalizaciones por pérdida de ventas. Por otro lado, se cuantifica explícitamente el coste de la coordinación teniendo en cuenta los ciclos de coordinación iterativos. El método se aplica a una configuración de cadena de suministro ejemplar considerando diversos parámetros. Los resultados de la simulación confirman que, en la mayoría de los casos, el beneficio aumenta cuando se intensifica la coordinación. Sin embargo, en ciertas situaciones en las que se aplican ciclos de planificación manuales e iterativos el coste de coordinación adicional no siempre conduce a mejor rendimiento logístico. Estos resultados inesperados no se pueden atribuir a ningún parámetro particular. La investigación confirma la gran importancia de nuevas dimensiones hasta ahora ignoradas en la evaluación de propuestas organizativas y herramientas de TI. A través del método heurístico se puede comparar de forma rápida, pero sólo aproximada, la eficiencia de diferentes formas de organización. Por el contrario, el método de simulación es más complejo pero da resultados más detallados, teniendo en cuenta parámetros específicos del contexto del caso concreto y del diseño organizativo. ABSTRACT Transactional systems such as Enterprise Resource Planning (ERP) systems have been implemented widely while analytical software like Supply Chain Management (SCM) add-ons are adopted less by manufacturing companies. Although significant benefits are reported stemming from SCM software implementations, companies are reluctant to invest in such systems. On the one hand this is due to the lack of methods that are able to detect benefits from the use of SCM software and on the other hand associated costs are not identified, detailed and quantified sufficiently. Coordination schemes based only on ERP systems are valid alternatives in industrial practice because significant investment in IT can be avoided. Therefore, the evaluation of these coordination procedures, in particular the cost due to iterations, is of high managerial interest and corresponding methods are comprehensive tools for strategic IT decision making. The purpose of this research is to provide evaluation methods that allow the comparison of different organizational forms and software support levels. The research begins with a comprehensive introduction dealing with the business environment that industrial networks are facing and concludes highlighting the challenges for the supply chain software industry. Afterwards, the central terminology is addressed, focusing on organization theory, IT investment peculiarities and supply chain management software typology. The literature review classifies recent supply chain management research referring to organizational design and its software support. The classification encompasses criteria related to research methodology and content. Empirical studies from management science focus on network types and organizational fit. Novel planning algorithms and innovative coordination schemes are developed mostly in the field of operations research in order to propose new software features. Operations and production management researchers realize cost-benefit analysis of IT software implementations. The literature review reveals that the success of software solutions for network coordination depends strongly on the fit of three dimensions: network configuration, coordination scheme and software functionality. Reviewed literature is mostly centered on the benefits of SCM software implementations. However, ERP system based supply chain coordination is still widespread industrial practice but the associated coordination cost has not been addressed by researchers. Fundamentals of efficient organizational design are explained in detail as far as required for the understanding of the synthesis of different organizational forms. Several coordination schemes have been shaped through the variation of the following design parameters: organizational structuring, coordination mechanisms and software support. The different organizational proposals are evaluated using a heuristic approach and a simulation-based method. For both cases, the principles of organization theory are respected. A lack of performance is due to dependencies between activities which are not managed properly. Therefore, within the heuristic method, dependencies are classified and their intensity is measured based on contextual factors. Afterwards the suitability of each organizational design element for the management of a specific dependency is determined. Finally, each organizational form is evaluated based on the contribution of the sum of design elements to coordination benefit and to coordination cost. Coordination benefit refers to improvement in logistic performance – this is the core concept of most supply chain evaluation models. Unfortunately, coordination cost which must be incurred to achieve benefits is usually not considered in detail. Iterative processes are costly when manually executed. This is the case when SCM software is not implemented and the ERP system is the only available coordination instrument. The heuristic model provides a simplified procedure for the classification of dependencies, quantification of influence factors and systematic search for adequate organizational forms and IT support. Discrete event simulation is applied in the second evaluation model using the software package ‘Plant Simulation’. On the one hand logistic performance is measured by manufacturing, inventory and transportation cost and penalties for lost sales. On the other hand coordination cost is explicitly considered taking into account iterative coordination cycles. The method is applied to an exemplary supply chain configuration considering various parameter settings. The simulation results confirm that, in most cases, benefit increases when coordination is intensified. However, in some situations when manual, iterative planning cycles are applied, additional coordination cost does not always lead to improved logistic performance. These unexpected results cannot be attributed to any particular parameter. The research confirms the great importance of up to now disregarded dimensions when evaluating SCM concepts and IT tools. The heuristic method provides a quick, but only approximate comparison of coordination efficiency for different organizational forms. In contrast, the more complex simulation method delivers detailed results taking into consideration specific parameter settings of network context and organizational design.

Arquitectura de supercomputación en la nube para la resolución de problemas de optimización combinatoria

La tesis está focalizada en la resolución de problemas de optimización combinatoria, haciendo uso de las opciones tecnológicas actuales que ofrecen las tecnologías de la información y las comunicaciones, y la investigación operativa. Los problemas de optimización combinatoria se resuelven en general mediante programación lineal y metaheurísticas. La aplicación de las técnicas de resolución de los problemas de optimización combinatoria requiere de una elevada carga computacional, y los algoritmos deben diseñarse, por un lado pensando en la efectividad para encontrar buenas soluciones del problema, y por otro lado, pensando en un uso adecuado de los recursos informáticos disponibles. La programación lineal y las metaheurísticas son técnicas de resolución genéricas, que se pueden aplicar a diferentes problemas, partiendo de una base común que se particulariza para cada problema concreto. En el campo del desarrollo de software, los frameworks cumplen esa función de comenzar un proyecto con el trabajo general ya disponible, con la opción de cambiar o extender ese comportamiento base o genérico, para construir el sistema concreto, lo que permite reducir el tiempo de desarrollo, y amplía las posibilidades de éxito del proyecto. En esta tesis se han desarrollado dos frameworks de desarrollo. El framework ILP permite modelar y resolver problemas de programación lineal, de forma independiente al software de resolución de programación lineal que se utilice. El framework LME permite resolver problemas de optimización combinatoria mediante metaheurísticas. Tradicionalmente, las aplicaciones de resolución de problemas de optimización combinatoria son aplicaciones de escritorio que permiten gestionar toda la información de entrada del problema y resuelven el problema en local, con los recursos hardware disponibles. Recientemente ha aparecido un nuevo paradigma de despliegue y uso de aplicaciones que permite compartir recursos informáticos especializados por Internet. Esta nueva forma de uso de recursos informáticos es la computación en la nube, que presenta el modelo de software como servicio (SaaS). En esta tesis se ha construido una plataforma SaaS, para la resolución de problemas de optimización combinatoria, que se despliega sobre arquitecturas compuestas por procesadores multi-núcleo y tarjetas gráficas, y dispone de algoritmos de resolución basados en frameworks de programación lineal y metaheurísticas. Toda la infraestructura es independiente del problema de optimización combinatoria a resolver, y se han desarrollado tres problemas que están totalmente integrados en la plataforma SaaS. Estos problemas se han seleccionado por su importancia práctica. Uno de los problemas tratados en la tesis, es el problema de rutas de vehículos (VRP), que consiste en calcular las rutas de menor coste de una flota de vehículos, que reparte mercancías a todos los clientes. Se ha partido de la versión más clásica del problema y se han hecho estudios en dos direcciones. Por un lado se ha cuantificado el aumento en la velocidad de ejecución de la resolución del problema en tarjetas gráficas. Por otro lado, se ha estudiado el impacto en la velocidad de ejecución y en la calidad de soluciones, en la resolución por la metaheurística de colonias de hormigas (ACO), cuando se introduce la programación lineal para optimizar las rutas individuales de cada vehículo. Este problema se ha desarrollado con los frameworks ILP y LME, y está disponible en la plataforma SaaS. Otro de los problemas tratados en la tesis, es el problema de asignación de flotas (FAP), que consiste en crear las rutas de menor coste para la flota de vehículos de una empresa de transporte de viajeros. Se ha definido un nuevo modelo de problema, que engloba características de problemas presentados en la literatura, y añade nuevas características, lo que permite modelar los requerimientos de las empresas de transporte de viajeros actuales. Este nuevo modelo resuelve de forma integrada el problema de definir los horarios de los trayectos, el problema de asignación del tipo de vehículo, y el problema de crear las rotaciones de los vehículos. Se ha creado un modelo de programación lineal para el problema, y se ha resuelto por programación lineal y por colonias de hormigas (ACO). Este problema se ha desarrollado con los frameworks ILP y LME, y está disponible en la plataforma SaaS. El último problema tratado en la tesis es el problema de planificación táctica de personal (TWFP), que consiste en definir la configuración de una plantilla de trabajadores de menor coste, para cubrir una demanda de carga de trabajo variable. Se ha definido un modelo de problema muy flexible en la definición de contratos, que permite el uso del modelo en diversos sectores productivos. Se ha definido un modelo matemático de programación lineal para representar el problema. Se han definido una serie de casos de uso, que muestran la versatilidad del modelo de problema, y permiten simular el proceso de toma de decisiones de la configuración de una plantilla de trabajadores, cuantificando económicamente cada decisión que se toma. Este problema se ha desarrollado con el framework ILP, y está disponible en la plataforma SaaS. ABSTRACT The thesis is focused on solving combinatorial optimization problems, using current technology options offered by information technology and communications, and operations research. Combinatorial optimization problems are solved in general by linear programming and metaheuristics. The application of these techniques for solving combinatorial optimization problems requires a high computational load, and algorithms are designed, on the one hand thinking to find good solutions to the problem, and on the other hand, thinking about proper use of the available computing resources. Linear programming and metaheuristic are generic resolution techniques, which can be applied to different problems, beginning with a common base that is particularized for each specific problem. In the field of software development, frameworks fulfill this function that allows you to start a project with the overall work already available, with the option to change or extend the behavior or generic basis, to build the concrete system, thus reducing the time development, and expanding the possibilities of success of the project. In this thesis, two development frameworks have been designed and developed. The ILP framework allows to modeling and solving linear programming problems, regardless of the linear programming solver used. The LME framework is designed for solving combinatorial optimization problems using metaheuristics. Traditionally, applications for solving combinatorial optimization problems are desktop applications that allow the user to manage all the information input of the problem and solve the problem locally, using the available hardware resources. Recently, a new deployment paradigm has appeared, that lets to share hardware and software resources by the Internet. This new use of computer resources is cloud computing, which presents the model of software as a service (SaaS). In this thesis, a SaaS platform has been built for solving combinatorial optimization problems, which is deployed on architectures, composed of multi-core processors and graphics cards, and has algorithms based on metaheuristics and linear programming frameworks. The SaaS infrastructure is independent of the combinatorial optimization problem to solve, and three problems are fully integrated into the SaaS platform. These problems have been selected for their practical importance. One of the problems discussed in the thesis, is the vehicle routing problem (VRP), which goal is to calculate the least cost of a fleet of vehicles, which distributes goods to all customers. The VRP has been studied in two directions. On one hand, it has been quantified the increase in execution speed when the problem is solved on graphics cards. On the other hand, it has been studied the impact on execution speed and quality of solutions, when the problem is solved by ant colony optimization (ACO) metaheuristic, and linear programming is introduced to optimize the individual routes of each vehicle. This problem has been developed with the ILP and LME frameworks, and is available in the SaaS platform. Another problem addressed in the thesis, is the fleet assignment problem (FAP), which goal is to create lower cost routes for a fleet of a passenger transport company. It has been defined a new model of problem, which includes features of problems presented in the literature, and adds new features, allowing modeling the business requirements of today's transport companies. This new integrated model solves the problem of defining the flights timetable, the problem of assigning the type of vehicle, and the problem of creating aircraft rotations. The problem has been solved by linear programming and ACO. This problem has been developed with the ILP and LME frameworks, and is available in the SaaS platform. The last problem discussed in the thesis is the tactical planning staff problem (TWFP), which is to define the staff of lower cost, to cover a given work load. It has been defined a very rich problem model in the definition of contracts, allowing the use of the model in various productive sectors. It has been defined a linear programming mathematical model to represent the problem. Some use cases has been defined, to show the versatility of the model problem, and to simulate the decision making process of setting up a staff, economically quantifying every decision that is made. This problem has been developed with the ILP framework, and is available in the SaaS platform.

Metodología para la optimización y análisis de la respuesta de medios e infraestructuras en el sistema aeroportuario en operaciones invernales mediante modelos basados en algorítmos genéticos

En este estudio, englobado dentro del campo de la investigación operacional en aeropuertos, se considera el problema de la optimización de la secuencia de descontaminación de nieve de los tramos que componen el área de maniobras de un aeropuerto, denominado RM-AM. Este problema se enfrenta a la optimización de recursos limitados para retirar la nieve de las calles de rodadura y pistas, dejándolas en un estado aceptable para la operación de aeronaves. El campo de vuelos se divide en subconjuntos de tramos significativos para la operación y se establecen tiempos objetivo de apertura al tráfico de aeronaves. Se desarrollan varios algoritmos matemáticos en los que se proponen distintas funciones objetivo, como son la hora de finalización del proceso, la suma de las horas de finalización de cada tramo, o el retraso entre la hora estimada y la hora de finalización. Durante este proceso, se van introduciendo restricciones operativas relativas al cumplimiento de objetivos operativos parciales aplicados a las zonas de especial interés, o relativas a la operación de los equipos de descontaminación. El problema se resuelve mediante optimización basada en programación lineal. Los resultados de las pruebas computacionales se hacen sobre cinco modelos de área de maniobras en los que va creciendo la complejidad y el tamaño. Se comparan las prestaciones de los distintos algoritmos. Una vez definido el modelo matemático para la optiamización, se propone una metodología estructurada para abordar dicho problema para cualquier área de manobras. Se define una estrategia en la operación. Se acomete el área de maniobras por zonas, con la condición de que los subconjuntos de tramos significativos queden englobados dentro de una sola de estas zonas. El problema se resuelve mediante un proceso iterativo de optimización aplicado sucesivamente a las zonas que componen el área de maniobras durante cada iteración. Se analiza la repercusión de los resultados en los procesos DMAN, AMAN y TP, para la integración de los resultados en el cálculo de TSAT y EBIT. El método se particulariza para el caso del área de maniobras del Aeropuerto Adolfo Suárez Madrid Barajas. ABSTRACT This study, which lies within the field of operations research in airports, considers the optimisation of the sequence for clearing snow from stretches of the manoeuvring area of an airport, known as RM-AM. This issue involves the optimisation of limited resources to remove snow from taxiways and runways thereby leaving them in an acceptable condition for operating aircraft. The airfield is divided into subsets of significant stretches for the purpose of operations and target times are established during which these are open to aircraft traffic. The study contains several mathematical models each with different functions, such as the end time of the process, the sum of the end times of each stretch, and gap between the estimated and the real end times. During this process, we introduce different operating restrictions on partial fulfilment of the operational targets as applied to zones of special interest, or relating to the operation of the snow-clearing machines. The problem is solved by optimisation based on linear programming. Computational tests are carried out on five distinct models of the manoeuvring area, which cover increasingly complex situations and larger areas. The different algorithms are then compared to one other. Having defined the mathematical model for the optimisation, we then set out a structured methodology to deal with any type of manoeuvring area. In other words, we define an operational strategy. The airfield is divided into subsets of significant stretches for the purpose of operations and target times are set at which these are to be open to aircraft traffic. The manoeuvring area is also divided into zones, with the condition that the subsets of significant stretches lie within just one of these zones. The problem is solved by an iterative optimisation process based on linear programming applied successively to the zones that make up the manoeuvring area during each iteration. The impact of the results on DMAN, AMAN and TP processes is analysed for their integration into the calculation of TSAT and EBIT. The method is particularized for the case of the manoeuvring area of Adolfo Suarez Madrid - Barajas Airport.

UMA ANÁLISE DA RELAÇÃO ENTRE VARIÁVEIS MACROECONÔMICAS E O COMPORTAMENTO DAS AÇÕES DE MAIOR LIQUIDEZ DO ÍNDICE IBOVESPA

As ações de maior liquidez do índice IBOVESPA, refletem o comportamento das ações de um modo geral, bem como a relação das variáveis macroeconômicas em seu comportamento e estão entre as mais negociadas no mercado de capitais brasileiro. Desta forma, pode-se entender que há reflexos de fatores que impactam as empresas de maior liquidez que definem o comportamento das variáveis macroeconômicas e que o inverso também é uma verdade, oscilações nos fatores macroeconômicos também afetam as ações de maior liquidez, como IPCA, PIB, SELIC e Taxa de Câmbio. O estudo propõe uma análise da relação existente entre variáveis macroeconômicas e o comportamento das ações de maior liquidez do índice IBOVESPA, corroborando com estudos que buscam entender a influência de fatores macroeconômicos sobre o preço de ações e contribuindo empiricamente com a formação de portfólios de investimento. O trabalho abrangeu o período de 2008 a 2014. Os resultados concluíram que a formação de carteiras, visando a proteção do capital investido, deve conter ativos com correlação negativa em relação às variáveis estudadas, o que torna possível a composição de uma carteira com risco reduzido.