MODELS AND SOLUTION ALGORITHMS FOR EQUITABLE RESOURCE ALLOCATION IN AIR TRAFFIC FLOW MANAGEMENT

Population growth and economic development lead to increasing demand for travel and pose mobility challenges on capacity-limited air traffic networks. The U.S. National Airspace System (NAS) has been operated near the capacity, and air traffic congestion is expected to remain as a top concern for the related system operators, passengers and airlines. This dissertation develops a number of model reformulations and efficient solution algorithms to address resource allocation problems in air traffic flow management, while explicitly accounting for equitable objectives in order to encourage further collaborations by different stakeholders. This dissertation first develops a bi-criteria optimization model to offload excess demand from different competing airlines in the congested airspace when the predicted traffic demand is higher than available capacity. Computationally efficient network flow models with side constraints are developed and extensively tested using datasets obtained from the Enhanced Traffic Management System (ETMS) database (now known as the Traffic Flow Management System). Representative Pareto-optimal tradeoff frontiers are consequently generated to allow decision-makers to identify best-compromising solutions based on relative weights and systematical considerations of both efficiency and equity. This dissertation further models and solves an integrated flight re-routing problem on an airspace network. Given a network of airspace sectors with a set of waypoint entries and a set of flights belonging to different air carriers, the optimization model aims to minimize the total flight travel time subject to a set of flight routing equity, operational and safety requirements. A time-dependent network flow programming formulation is proposed with stochastic sector capacities and rerouting equity for each air carrier as side constraints. A Lagrangian relaxation based method is used to dualize these constraints and decompose the original complex problem into a sequence of single flight rerouting/scheduling problems. Finally, within a multi-objective utility maximization framework, the dissertation proposes several practically useful heuristic algorithms for the long-term airport slot assignment problem. Alternative models are constructed to decompose the complex model into a series of hourly assignment sub-problems. A new paired assignment heuristic algorithm is developed to adapt the round robin scheduling principle for improving fairness measures across different airlines. Computational results are presented to show the strength of each proposed modeling approach

Shared Mobility Optimization in Large Scale Transportation Networks: Methodology and Applications

abstract: Optimization of on-demand transportation systems and ride-sharing services involves solving a class of complex vehicle routing problems with pickup and delivery with time windows (VRPPDTW). Previous research has made a number of important contributions to the challenging pickup and delivery problem along different formulation or solution approaches. However, there are a number of modeling and algorithmic challenges for a large-scale deployment of a vehicle routing and scheduling algorithm, especially for regional networks with various road capacity and traffic delay constraints on freeway bottlenecks and signal timing on urban streets. The main thrust of this research is constructing hyper-networks to implicitly impose complicated constraints of a vehicle routing problem (VRP) into the model within the network construction. This research introduces a new methodology based on hyper-networks to solve the very important vehicle routing problem for the case of generic ride-sharing problem. Then, the idea of hyper-networks is applied for (1) solving the pickup and delivery problem with synchronized transfers, (2) computing resource hyper-prisms for sustainable transportation planning in the field of time-geography, and (3) providing an integrated framework that fully captures the interactions between supply and demand dimensions of travel to model the implications of advanced technologies and mobility services on traveler behavior.Dissertation/ThesisDoctoral Dissertation Civil, Environmental and Sustainable Engineering 201

Models and Algorithms for Addressing Travel Time Variability: Applications from Optimal Path Finding and Traffic Equilibrium Problems

An optimal path finding problem and a traffic equilibrium problem are two important, fundamental, and interrelated topics in the transportation research field. Under travel time variability, the road networks are considered as stochastic, where the link travel times are treated as random variables with known probability density functions. By considering the effect of travel time variability and corresponding risk-taking behavior of the travelers, this dissertation proposes models and algorithms for addressing travel time variability with applications from optimal path finding and traffic equilibrium problems. Specifically, two new optimal path finding models and two novel traffic equilibrium models are proposed in stochastic networks. To adaptively determine a reliable path with the minimum travel time budget required to meet the user-specified reliability threshold α, an adaptive α-reliable path finding model is proposed. It is formulated as a chance constrained model under a dynamic programming framework. Then, a discrete-time algorithm is developed based on the properties of the proposed model. In addition to accounting for the reliability aspect of travel time variability, the α-reliable mean-excess path finding model further concerns the unreliability aspect of the late trips beyond the travel time budget. It is formulated as a stochastic mixed-integer nonlinear program. To solve this difficult problem, a practical double relaxation procedure is developed. By recognizing travelers are not only interested in saving their travel time but also in reducing their risk of being late, a α-reliable mean-excess traffic equilibrium (METE) model is proposed. Furthermore, a stochastic α-reliable mean-excess traffic equilibrium (SMETE) model is developed by incorporating the travelers’ perception error, where the travelers’ route choice decisions are determined by the perceived distribution of the stochastic travel time. Both models explicitly examine the effects of both reliability and unreliability aspects of travel time variability in a network equilibrium framework. They are both formulated as a variational inequality (VI) problem and solved by a route-based algorithm based on the modified alternating direction method. In conclusion, this study explores the effects of the various aspects (reliability and unreliability) of travel time variability on travelers’ route choice decision process by considering their risk preferences. The proposed models provide novel views of the optimal path finding problem and the traffic equilibrium problem under an uncertain environment, and the proposed solution algorithms enable potential applicability for solving practical problems

Mathematical programming models to design and analyse efficient and robust raiway freight transport networks

(English) Searching to achieve an ambitious reduction in greenhouse gas emissions, the European Union has set as a goal a modal shift in freight transport of 30\% by rail or waterborne for the near future. The increasing efforts of many governments to intensify rail freight transport often must face the difficulties involved in improving both infrastructure and rail operations. Moreover, infrastructure management and business operations usually correspond to different entities with highly contradictory economic interests. Making progress on the reliability of the railway network is one of the main factors to be considered to make the use of the train more attractive as a means of transport for industry. Also, focusing on shippers' response to road and rail competition and the role of different rail undertakings competing with each other may help boost the use of rail for freight transport. Seeking to reinforce these two goals, this thesis introduces two independent mathematical optimisation models, which may also be complementary, and which have been developed under a common conceptual framework of data structures and variables to guarantee their compatibility. The first model is a mathematical programming-based design model for evaluating the impact on a mixed railway network from proposals for infrastructure improvement and capacity expansion that are oriented mainly toward increasing freight transportation. The model has been applied to extend elements of an existing mixed railway network, perform relatively less costly actions on the network, and enhance capacity by adding new blocking/control systems at specific locations. These aspects are usually not considered in models for regional planning. Rather than a model whose sole focus is on railway capacity expansion, this approach combines capacity-expansion with network design. Because the way investments generate returns to the freight transportation system is of utmost relevance for these types of problems, this model is based on the efficient frontier between investment and operating costs. The second model is a combined model for jointly evaluating the modal split road-rail, and the resulting railway freight flows on the railway network. This combined modal split-traffic assignment model is addressed to the case when a modal split based on a random utility model is available, and some of its coefficients may present a non-negligible variability. To this end, after the initial deterministic formulation, a robust counterpart of the model is developed. The model, formulated as a non-linear integer programming problem, is oriented to a multi-carrier environment and includes constraints to consider the interactions between the different types of flows on the railway network, allowing a detailed evaluation of the cost types of the carriers and the network capacity. An algorithmic solution based on the outer approximation method is shown to provide accurate solutions in a reasonable computational time for the robust and non-robust versions of the model. Examples centred on a section of the Trans-European Transport Network, the TEN-T Core network corridors, are reported to test the applicability of the models. Results show the effectiveness of both models. The design model can be a helpful tool for analysing the impact infrastructure investments may have on operating costs, where (implicit) capacity limitations in the scenarios to be evaluated may necessarily be taken into account. At the same time, it can be complemented with the combined modal split-traffic assignment model by assessing the possible shippers' response to the different railway carriers' services competing with each other and the road.(Español) Tratando de lograr una significativa y ambiciosa reducción de las emisiones de gases de efecto invernadero, la Unión Europea se ha marcado como objetivo que los modos de transporte de mercancías alternativos a la carretera, como el ferrocarril o la navegación fluvial, alcancen una cuota del 30% sobre el total de mercancías transportadas por tierra en Europa en los próximos años. Los crecientes esfuerzos que llevan a cabo los diferentes gobiernos se enfrentan con demasiada frecuencia con las dificultades que suponen mejorar de forma simultánea infraestructura y operaciones ferroviarias, habitualmente gestionados por entes diferentes con intereses económicos enfrentados. Mejorar la fiabilidad de la red ferroviaria es uno de los principales factores a tener en cuenta para hacer más atractivo el uso del tren como medio de transporte para la industria. Por otro lado, centrarse en los criterios que pueden llevar a las empresas a elegir entre carretera o tren, y en el papel que juegan las diferentes compañías ferroviarias en esta elección, compitiendo entre sí, puede ayudar a incrementar el uso del tren para el transporte de mercancías. Con la idea de reforzar estos dos objetivos, este trabajo de tesis presenta dos modelos matemáticos de optimización, independientes pero a la vez complementarios, y desarrollados bajo un marco conceptual de estructuras de datos y variables común para garantizar su compatibilidad. El primer modelo es un modelo de diseño basado en programación matemática para evaluar el impacto que pueden tener, sobre una red ferroviaria de uso mixto, propuestas de mejora de la infraestructura y de ampliación de la capacidad dirigidas principalmente a incrementar el uso del tren para el transporte de mercancías. El modelo se ha orientado a la modificación de elementos de una red ferroviaria de uso mixto existente, proponiendo intervenciones en la red relativamente poco costosas, y aumentando la capacidad añadiendo nuevos sistemas de bloqueo y control en ubicaciones específicas. Para este tipo de problemas, es de la máxima relevancia la manera en que las inversiones generan retornos al sistema de transporte ferroviario. Por eso, este modelo está basado en el óptimo equilibrio entre la inversión y los costes de operación. El segundo modelo es un modelo combinado para evaluar de forma conjunta el reparto modal entre carretera y tren, y los flujos de mercancías en la red ferroviaria resultantes. Este modelo está enfocado hacia aquellas situaciones en que hay un modelo de utilidad aleatoria disponible, pero algunos de sus coeficientes pueden presentar una variabilidad que no debe ser ignorada. Con esta finalidad, tras la formulación inicial del modelo determinístico se presenta una versión robusta de la formulación. El modelo, formulado como un problema de programación no lineal entera, está enfocado hacia un entorno en el que conviven (y compiten) diferentes compañías ferroviarias. Se detalla un algoritmo para resolver el modelo, basado en el método de aproximaciones externas, que permite obtener soluciones precisas con un tiempo computacional razonable, tanto para la versión determinística como para la versión robusta. Ejemplos basados en una sección de la Red Trans-Europea de Transporte (TEN-T por sus siglas en inglés) permiten validar la aplicabilidad y eficacia de los modelos. El modelo de diseño puede ser una herramienta útil para analizar el impacto que las inversiones en infraestructura pueden tener en los costes de operación, teniendo en cuenta las limitaciones de capacidad que existen en los escenarios evaluados. De la misma forma, se puede complementar este análisis con el modelo combinado de reparto modal y asignación de flujos, en el que se puede comprobar la posible respuesta de las empresas que requieren transportar sus productos ante los diferentes servicios ofrecidos por las compañías ferroviarias compitiendo entre si, y compitiendo con la carretera.Estadística i investigació operativ

Mathematical programming models to design and analyse efficient and robust raiway freight transport networks

(English) Searching to achieve an ambitious reduction in greenhouse gas emissions, the European Union has set as a goal a modal shift in freight transport of 30\% by rail or waterborne for the near future. The increasing efforts of many governments to intensify rail freight transport often must face the difficulties involved in improving both infrastructure and rail operations. Moreover, infrastructure management and business operations usually correspond to different entities with highly contradictory economic interests. Making progress on the reliability of the railway network is one of the main factors to be considered to make the use of the train more attractive as a means of transport for industry. Also, focusing on shippers' response to road and rail competition and the role of different rail undertakings competing with each other may help boost the use of rail for freight transport. Seeking to reinforce these two goals, this thesis introduces two independent mathematical optimisation models, which may also be complementary, and which have been developed under a common conceptual framework of data structures and variables to guarantee their compatibility. The first model is a mathematical programming-based design model for evaluating the impact on a mixed railway network from proposals for infrastructure improvement and capacity expansion that are oriented mainly toward increasing freight transportation. The model has been applied to extend elements of an existing mixed railway network, perform relatively less costly actions on the network, and enhance capacity by adding new blocking/control systems at specific locations. These aspects are usually not considered in models for regional planning. Rather than a model whose sole focus is on railway capacity expansion, this approach combines capacity-expansion with network design. Because the way investments generate returns to the freight transportation system is of utmost relevance for these types of problems, this model is based on the efficient frontier between investment and operating costs. The second model is a combined model for jointly evaluating the modal split road-rail, and the resulting railway freight flows on the railway network. This combined modal split-traffic assignment model is addressed to the case when a modal split based on a random utility model is available, and some of its coefficients may present a non-negligible variability. To this end, after the initial deterministic formulation, a robust counterpart of the model is developed. The model, formulated as a non-linear integer programming problem, is oriented to a multi-carrier environment and includes constraints to consider the interactions between the different types of flows on the railway network, allowing a detailed evaluation of the cost types of the carriers and the network capacity. An algorithmic solution based on the outer approximation method is shown to provide accurate solutions in a reasonable computational time for the robust and non-robust versions of the model. Examples centred on a section of the Trans-European Transport Network, the TEN-T Core network corridors, are reported to test the applicability of the models. Results show the effectiveness of both models. The design model can be a helpful tool for analysing the impact infrastructure investments may have on operating costs, where (implicit) capacity limitations in the scenarios to be evaluated may necessarily be taken into account. At the same time, it can be complemented with the combined modal split-traffic assignment model by assessing the possible shippers' response to the different railway carriers' services competing with each other and the road.(Español) Tratando de lograr una significativa y ambiciosa reducción de las emisiones de gases de efecto invernadero, la Unión Europea se ha marcado como objetivo que los modos de transporte de mercancías alternativos a la carretera, como el ferrocarril o la navegación fluvial, alcancen una cuota del 30% sobre el total de mercancías transportadas por tierra en Europa en los próximos años. Los crecientes esfuerzos que llevan a cabo los diferentes gobiernos se enfrentan con demasiada frecuencia con las dificultades que suponen mejorar de forma simultánea infraestructura y operaciones ferroviarias, habitualmente gestionados por entes diferentes con intereses económicos enfrentados. Mejorar la fiabilidad de la red ferroviaria es uno de los principales factores a tener en cuenta para hacer más atractivo el uso del tren como medio de transporte para la industria. Por otro lado, centrarse en los criterios que pueden llevar a las empresas a elegir entre carretera o tren, y en el papel que juegan las diferentes compañías ferroviarias en esta elección, compitiendo entre sí, puede ayudar a incrementar el uso del tren para el transporte de mercancías. Con la idea de reforzar estos dos objetivos, este trabajo de tesis presenta dos modelos matemáticos de optimización, independientes pero a la vez complementarios, y desarrollados bajo un marco conceptual de estructuras de datos y variables común para garantizar su compatibilidad. El primer modelo es un modelo de diseño basado en programación matemática para evaluar el impacto que pueden tener, sobre una red ferroviaria de uso mixto, propuestas de mejora de la infraestructura y de ampliación de la capacidad dirigidas principalmente a incrementar el uso del tren para el transporte de mercancías. El modelo se ha orientado a la modificación de elementos de una red ferroviaria de uso mixto existente, proponiendo intervenciones en la red relativamente poco costosas, y aumentando la capacidad añadiendo nuevos sistemas de bloqueo y control en ubicaciones específicas. Para este tipo de problemas, es de la máxima relevancia la manera en que las inversiones generan retornos al sistema de transporte ferroviario. Por eso, este modelo está basado en el óptimo equilibrio entre la inversión y los costes de operación. El segundo modelo es un modelo combinado para evaluar de forma conjunta el reparto modal entre carretera y tren, y los flujos de mercancías en la red ferroviaria resultantes. Este modelo está enfocado hacia aquellas situaciones en que hay un modelo de utilidad aleatoria disponible, pero algunos de sus coeficientes pueden presentar una variabilidad que no debe ser ignorada. Con esta finalidad, tras la formulación inicial del modelo determinístico se presenta una versión robusta de la formulación. El modelo, formulado como un problema de programación no lineal entera, está enfocado hacia un entorno en el que conviven (y compiten) diferentes compañías ferroviarias. Se detalla un algoritmo para resolver el modelo, basado en el método de aproximaciones externas, que permite obtener soluciones precisas con un tiempo computacional razonable, tanto para la versión determinística como para la versión robusta. Ejemplos basados en una sección de la Red Trans-Europea de Transporte (TEN-T por sus siglas en inglés) permiten validar la aplicabilidad y eficacia de los modelos. El modelo de diseño puede ser una herramienta útil para analizar el impacto que las inversiones en infraestructura pueden tener en los costes de operación, teniendo en cuenta las limitaciones de capacidad que existen en los escenarios evaluados. De la misma forma, se puede complementar este análisis con el modelo combinado de reparto modal y asignación de flujos, en el que se puede comprobar la posible respuesta de las empresas que requieren transportar sus productos ante los diferentes servicios ofrecidos por las compañías ferroviarias compitiendo entre si, y compitiendo con la carretera.Postprint (published version

Cross-comparison of convergence algorithms to solve trip-based dynamic traffic assignment problems

Solving a dynamic traffic assignment problem in a transportation network is a computational challenge. This study first reviews the different algorithms in the literature used to numerically calculate the User Equilibrium (UE) related to dynamic network loading. Most of them are based on iterative methods to solve a fixed-point problem. Two elements must be computed: the path set and the optimal path flow distribution between all origin-destination pairs. In a generic framework these two steps are referred to as the outer and the inner loops, respectively. The goal of this study is to assess the computational performance of the inner loop methods that calculate the path flow distribution for different network settings (mainly network size and demand levels). Several improvements are also proposed to speed up convergence: four new swapping algorithms and two new methods for the step size initialization used in each descent iteration. All these extensions significantly reduce the number of iterations to obtain a good convergence rate and drastically speed up the overall simulations. The results show that the performance of different components of the solution algorithm is sensitive to the network size and saturation. Finally, the best algorithms and settings are identified for all network sizes with particular attention being given to the largest scale

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order