An application of linear programming in the pottery industry

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A fuzzy AHP based integer linear programming model for the multi-criteria transshipment problem

Purpose – The purpose of this research is to develop a holistic approach to maximize the customer service level while minimizing the logistics cost by using an integrated multiple criteria decision making (MCDM) method for the contemporary transshipment problem. Unlike the prevalent optimization techniques, this paper proposes an integrated approach which considers both quantitative and qualitative factors in order to maximize the benefits of service deliverers and customers under uncertain environments. Design/methodology/approach – This paper proposes a fuzzy-based integer linear programming model, based on the existing literature and validated with an example case. The model integrates the developed fuzzy modification of the analytic hierarchy process (FAHP), and solves the multi-criteria transshipment problem. Findings – This paper provides several novel insights about how to transform a company from a cost-based model to a service-dominated model by using an integrated MCDM method. It suggests that the contemporary customer-driven supply chain remains and increases its competitiveness from two aspects: optimizing the cost and providing the best service simultaneously. Research limitations/implications – This research used one illustrative industry case to exemplify the developed method. Considering the generalization of the research findings and the complexity of the transshipment service network, more cases across multiple industries are necessary to further enhance the validity of the research output. Practical implications – The paper includes implications for the evaluation and selection of transshipment service suppliers, the construction of optimal transshipment network as well as managing the network. Originality/value – The major advantages of this generic approach are that both quantitative and qualitative factors under fuzzy environment are considered simultaneously and also the viewpoints of service deliverers and customers are focused. Therefore, it is believed that it is useful and applicable for the transshipment service network design.

Integer Linear Programming for Sequence Problems: A general approach to reduce the problem size

Sequence problems belong to the most challenging interdisciplinary topics of the actuality. They are ubiquitous in science and daily life and occur, for example, in form of DNA sequences encoding all information of an organism, as a text (natural or formal) or in form of a computer program. Therefore, sequence problems occur in many variations in computational biology (drug development), coding theory, data compression, quantitative and computational linguistics (e.g. machine translation). In recent years appeared some proposals to formulate sequence problems like the closest string problem (CSP) and the farthest string problem (FSP) as an Integer Linear Programming Problem (ILPP). In the present talk we present a general novel approach to reduce the size of the ILPP by grouping isomorphous columns of the string matrix together. The approach is of practical use, since the solution of sequence problems is very time consuming, in particular when the sequences are long.

Revenue Management in Make-To-Order Manufacturing: Case Study of Capacity Control at ThyssenKrupp VDM

While revenue management (RM) is traditionally considered a tool of service operations, RM shows considerable potential for application in manufacturing operations. The typical challenges in make-to-order manufacturing are fixed manufacturing capacities and a great variety in offered products, going along with pronounced fluctuations in demand and profitability. Since Harris and Pinder in the mid-90s, numerous papers have furthered the understanding of RM theory in this environment. Nevertheless, results to be expected from applying the developed methods to a practical industry setting have yet to be reported. To this end, this paper investigates a possible application of RM at ThyssenKrupp VDM, leading to considerable improvements in several areas.

Efficient certification of feasibility and objective value of linear programs and its applications

The use of linear programming in various areas has increased with the significant improvement of specialized solvers. Linear programs are used as such to model practical problems, or as subroutines in algorithms such as formal proofs or branch-and-cut frameworks. In many situations a certified answer is needed, for example the guarantee that the linear program is feasible or infeasible, or a provably safe bound on its objective value. Most of the available solvers work with floating-point arithmetic and are thus subject to its shortcomings such as rounding errors or underflow, therefore they can deliver incorrect answers. While adequate for some applications, this is unacceptable for critical applications like flight controlling or nuclear plant management due to the potential catastrophic consequences. We propose a method that gives a certified answer whether a linear program is feasible or infeasible, or returns unknown'. The advantage of our method is that it is reasonably fast and rarely answers unknown'. It works by computing a safe solution that is in some way the best possible in the relative interior of the feasible set. To certify the relative interior, we employ exact arithmetic, whose use is nevertheless limited in general to critical places, allowing us to rnremain computationally efficient. Moreover, when certain conditions are fulfilled, our method is able to deliver a provable bound on the objective value of the linear program. We test our algorithm on typical benchmark sets and obtain higher rates of success compared to previous approaches for this problem, while keeping the running times acceptably small. The computed objective value bounds are in most of the cases very close to the known exact objective values. We prove the usability of the method we developed by additionally employing a variant of it in a different scenario, namely to improve the results of a Satisfiability Modulo Theories solver. Our method is used as a black box in the nodes of a branch-and-bound tree to implement conflict learning based on the certificate of infeasibility for linear programs consisting of subsets of linear constraints. The generated conflict clauses are in general small and give good rnprospects for reducing the search space. Compared to other methods we obtain significant improvements in the running time, especially on the large instances.

Integrated parallelization of computations and visualization for large-scale applications

Critical applications like cyclone tracking and earthquake modeling require simultaneous high-performance simulations and online visualization for timely analysis. Faster simulations and simultaneous visualization enable scientists provide real-time guidance to decision makers. In this work, we have developed an integrated user-driven and automated steering framework that simultaneously performs numerical simulations and efficient online remote visualization of critical weather applications in resource-constrained environments. It considers application dynamics like the criticality of the application and resource dynamics like the storage space, network bandwidth and available number of processors to adapt various application and resource parameters like simulation resolution, simulation rate and the frequency of visualization. We formulate the problem of finding an optimal set of simulation parameters as a linear programming problem. This leads to 30% higher simulation rate and 25-50% lesser storage consumption than a naive greedy approach. The framework also provides the user control over various application parameters like region of interest and simulation resolution. We have also devised an adaptive algorithm to reduce the lag between the simulation and visualization times. Using experiments with different network bandwidths, we find that our adaptive algorithm is able to reduce lag as well as visualize the most representative frames.

Dynamic Facility Location with Modular Capacities : Models, Algorithms and Applications in Forestry

Les décisions de localisation sont souvent soumises à des aspects dynamiques comme des changements dans la demande des clients. Pour y répondre, la solution consiste à considérer une flexibilité accrue concernant l’emplacement et la capacité des installations. Même lorsque la demande est prévisible, trouver le planning optimal pour le déploiement et l'ajustement dynamique des capacités reste un défi. Dans cette thèse, nous nous concentrons sur des problèmes de localisation avec périodes multiples, et permettant l'ajustement dynamique des capacités, en particulier ceux avec des structures de coûts complexes. Nous étudions ces problèmes sous différents points de vue de recherche opérationnelle, en présentant et en comparant plusieurs modèles de programmation linéaire en nombres entiers (PLNE), l'évaluation de leur utilisation dans la pratique et en développant des algorithmes de résolution efficaces. Cette thèse est divisée en quatre parties. Tout d’abord, nous présentons le contexte industriel à l’origine de nos travaux: une compagnie forestière qui a besoin de localiser des campements pour accueillir les travailleurs forestiers. Nous présentons un modèle PLNE permettant la construction de nouveaux campements, l’extension, le déplacement et la fermeture temporaire partielle des campements existants. Ce modèle utilise des contraintes de capacité particulières, ainsi qu’une structure de coût à économie d’échelle sur plusieurs niveaux. L'utilité du modèle est évaluée par deux études de cas. La deuxième partie introduit le problème dynamique de localisation avec des capacités modulaires généralisées. Le modèle généralise plusieurs problèmes dynamiques de localisation et fournit de meilleures bornes de la relaxation linéaire que leurs formulations spécialisées. Le modèle peut résoudre des problèmes de localisation où les coûts pour les changements de capacité sont définis pour toutes les paires de niveaux de capacité, comme c'est le cas dans le problème industriel mentionnée ci-dessus. Il est appliqué à trois cas particuliers: l'expansion et la réduction des capacités, la fermeture temporaire des installations, et la combinaison des deux. Nous démontrons des relations de dominance entre notre formulation et les modèles existants pour les cas particuliers. Des expériences de calcul sur un grand nombre d’instances générées aléatoirement jusqu’à 100 installations et 1000 clients, montrent que notre modèle peut obtenir des solutions optimales plus rapidement que les formulations spécialisées existantes. Compte tenu de la complexité des modèles précédents pour les grandes instances, la troisième partie de la thèse propose des heuristiques lagrangiennes. Basées sur les méthodes du sous-gradient et des faisceaux, elles trouvent des solutions de bonne qualité même pour les instances de grande taille comportant jusqu’à 250 installations et 1000 clients. Nous améliorons ensuite la qualité de la solution obtenue en résolvent un modèle PLNE restreint qui tire parti des informations recueillies lors de la résolution du dual lagrangien. Les résultats des calculs montrent que les heuristiques donnent rapidement des solutions de bonne qualité, même pour les instances où les solveurs génériques ne trouvent pas de solutions réalisables. Finalement, nous adaptons les heuristiques précédentes pour résoudre le problème industriel. Deux relaxations différentes sont proposées et comparées. Des extensions des concepts précédents sont présentées afin d'assurer une résolution fiable en un temps raisonnable.

Scheduling Grid Applications with Software Requirements

The aim of task scheduling is to minimize the makespan of applications, exploiting the best possible way to use shared resources. Applications have requirements which call for customized environments for their execution. One way to provide such environments is to use virtualization on demand. This paper presents two schedulers based on integer linear programming which schedule virtual machines (VMs) in grid resources and tasks on these VMs. The schedulers differ from previous work by the joint scheduling of tasks and VMs and by considering the impact of the available bandwidth on the quality of the schedule. Experiments show the efficacy of the schedulers in scenarios with different network configurations.

Programação linear por partes: revisão teórica e aplicações

Procura-se resgatar a importância de uma subárea da Programação Matemática conhecida como Programação Linear Por Partes - PLP. de fato a PLP tem inúmeras aplicações tanto na área teórica como em situações reais. Este trabalho apresenta os resultados de uma pesquisa bibliográfica, efetuada nas principais revistas técnicas e livros disponíveis relacionados com Pesquisa Operacional, que visou situar o estado da'arte da Programação Linear por Partes, bem como a abrangência de sua aplicabilidade. Particularmente, no contexto da PLP, este texto deslaca a Programação em Redes Lineares por Partes devido a sua relevância em muitas situações práticas.

Programação linear à criação de planejamentos otimizados em radioterapia

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Valuation concepts and techniques with applications to coastal resources

Includes bibliography

Linear matrix inequality-based robust model predictive control for time-delayed systems

This work addresses the solution to the problem of robust model predictive control (MPC) of systems with model uncertainty. The case of zone control of multi-variable stable systems with multiple time delays is considered. The usual approach of dealing with this kind of problem is through the inclusion of non-linear cost constraint in the control problem. The control action is then obtained at each sampling time as the solution to a non-linear programming (NLP) problem that for high-order systems can be computationally expensive. Here, the robust MPC problem is formulated as a linear matrix inequality problem that can be solved in real time with a fraction of the computer effort. The proposed approach is compared with the conventional robust MPC and tested through the simulation of a reactor system of the process industry.

Enhanced Mixed Integer Programming Techniques and Routing Problems

Mixed integer programming is up today one of the most widely used techniques for dealing with hard optimization problems. On the one side, many practical optimization problems arising from real-world applications (such as, e.g., scheduling, project planning, transportation, telecommunications, economics and finance, timetabling, etc) can be easily and effectively formulated as Mixed Integer linear Programs (MIPs). On the other hand, 50 and more years of intensive research has dramatically improved on the capability of the current generation of MIP solvers to tackle hard problems in practice. However, many questions are still open and not fully understood, and the mixed integer programming community is still more than active in trying to answer some of these questions. As a consequence, a huge number of papers are continuously developed and new intriguing questions arise every year. When dealing with MIPs, we have to distinguish between two different scenarios. The first one happens when we are asked to handle a general MIP and we cannot assume any special structure for the given problem. In this case, a Linear Programming (LP) relaxation and some integrality requirements are all we have for tackling the problem, and we are ``forced" to use some general purpose techniques. The second one happens when mixed integer programming is used to address a somehow structured problem. In this context, polyhedral analysis and other theoretical and practical considerations are typically exploited to devise some special purpose techniques. This thesis tries to give some insights in both the above mentioned situations. The first part of the work is focused on general purpose cutting planes, which are probably the key ingredient behind the success of the current generation of MIP solvers. Chapter 1 presents a quick overview of the main ingredients of a branch-and-cut algorithm, while Chapter 2 recalls some results from the literature in the context of disjunctive cuts and their connections with Gomory mixed integer cuts. Chapter 3 presents a theoretical and computational investigation of disjunctive cuts. In particular, we analyze the connections between different normalization conditions (i.e., conditions to truncate the cone associated with disjunctive cutting planes) and other crucial aspects as cut rank, cut density and cut strength. We give a theoretical characterization of weak rays of the disjunctive cone that lead to dominated cuts, and propose a practical method to possibly strengthen those cuts arising from such weak extremal solution. Further, we point out how redundant constraints can affect the quality of the generated disjunctive cuts, and discuss possible ways to cope with them. Finally, Chapter 4 presents some preliminary ideas in the context of multiple-row cuts. Very recently, a series of papers have brought the attention to the possibility of generating cuts using more than one row of the simplex tableau at a time. Several interesting theoretical results have been presented in this direction, often revisiting and recalling other important results discovered more than 40 years ago. However, is not clear at all how these results can be exploited in practice. As stated, the chapter is a still work-in-progress and simply presents a possible way for generating two-row cuts from the simplex tableau arising from lattice-free triangles and some preliminary computational results. The second part of the thesis is instead focused on the heuristic and exact exploitation of integer programming techniques for hard combinatorial optimization problems in the context of routing applications. Chapters 5 and 6 present an integer linear programming local search algorithm for Vehicle Routing Problems (VRPs). The overall procedure follows a general destroy-and-repair paradigm (i.e., the current solution is first randomly destroyed and then repaired in the attempt of finding a new improved solution) where a class of exponential neighborhoods are iteratively explored by heuristically solving an integer programming formulation through a general purpose MIP solver. Chapters 7 and 8 deal with exact branch-and-cut methods. Chapter 7 presents an extended formulation for the Traveling Salesman Problem with Time Windows (TSPTW), a generalization of the well known TSP where each node must be visited within a given time window. The polyhedral approaches proposed for this problem in the literature typically follow the one which has been proven to be extremely effective in the classical TSP context. Here we present an overall (quite) general idea which is based on a relaxed discretization of time windows. Such an idea leads to a stronger formulation and to stronger valid inequalities which are then separated within the classical branch-and-cut framework. Finally, Chapter 8 addresses the branch-and-cut in the context of Generalized Minimum Spanning Tree Problems (GMSTPs) (i.e., a class of NP-hard generalizations of the classical minimum spanning tree problem). In this chapter, we show how some basic ideas (and, in particular, the usage of general purpose cutting planes) can be useful to improve on branch-and-cut methods proposed in the literature.

Networks, Uncertainty, Applications and a Crusade for Optimality

In this thesis we address a collection of Network Design problems which are strongly motivated by applications from Telecommunications, Logistics and Bioinformatics. In most cases we justify the need of taking into account uncertainty in some of the problem parameters, and different Robust optimization models are used to hedge against it. Mixed integer linear programming formulations along with sophisticated algorithmic frameworks are designed, implemented and rigorously assessed for the majority of the studied problems. The obtained results yield the following observations: (i) relevant real problems can be effectively represented as (discrete) optimization problems within the framework of network design; (ii) uncertainty can be appropriately incorporated into the decision process if a suitable robust optimization model is considered; (iii) optimal, or nearly optimal, solutions can be obtained for large instances if a tailored algorithm, that exploits the structure of the problem, is designed; (iv) a systematic and rigorous experimental analysis allows to understand both, the characteristics of the obtained (robust) solutions and the behavior of the proposed algorithm.

Applications of Formal Languages to Management of Manned and Unmanned Aircraft

En el futuro, la gestión del tráfico aéreo (ATM, del inglés air traffic management) requerirá un cambio de paradigma, de la gestión principalmente táctica de hoy, a las denominadas operaciones basadas en trayectoria. Un incremento en el nivel de automatización liberará al personal de ATM —controladores, tripulación, etc.— de muchas de las tareas que realizan hoy. Las personas seguirán siendo el elemento central en la gestión del tráfico aéreo del futuro, pero lo serán mediante la gestión y toma de decisiones. Se espera que estas dos mejoras traigan un incremento en la eficiencia de la gestión del tráfico aéreo que permita hacer frente al incremento previsto en la demanda de transporte aéreo. Para aplicar el concepto de operaciones basadas en trayectoria, el usuario del espacio aéreo (la aerolínea, piloto, u operador) y el proveedor del servicio de navegación aérea deben negociar las trayectorias mediante un proceso de toma de decisiones colaborativo. En esta negociación, es necesaria una forma adecuada de compartir dichas trayectorias. Compartir la trayectoria completa requeriría un gran ancho de banda, y la trayectoria compartida podría invalidarse si cambiase la predicción meteorológica. En su lugar, podría compartirse una descripción de la trayectoria independiente de las condiciones meteorológicas, de manera que la trayectoria real se pudiese calcular a partir de dicha descripción. Esta descripción de la trayectoria debería ser fácil de procesar usando un programa de ordenador —ya que parte del proceso de toma de decisiones estará automatizado—, pero también fácil de entender para un operador humano —que será el que supervise el proceso y tome las decisiones oportunas—. Esta tesis presenta una serie de lenguajes formales que pueden usarse para este propósito. Estos lenguajes proporcionan los medios para describir trayectorias de aviones durante todas las fases de vuelo, desde la maniobra de push-back (remolcado hasta la calle de rodaje), hasta la llegada a la terminal del aeropuerto de destino. También permiten describir trayectorias tanto de aeronaves tripuladas como no tripuladas, incluyendo aviones de ala fija y cuadricópteros. Algunos de estos lenguajes están estrechamente relacionados entre sí, y organizados en una jerarquía. Uno de los lenguajes fundamentales de esta jerarquía, llamado aircraft intent description language (AIDL), ya había sido desarrollado con anterioridad a esta tesis. Este lenguaje fue derivado de las ecuaciones del movimiento de los aviones de ala fija, y puede utilizarse para describir sin ambigüedad trayectorias de este tipo de aeronaves. Una variante de este lenguaje, denominada quadrotor AIDL (QR-AIDL), ha sido desarrollada en esta tesis para permitir describir trayectorias de cuadricópteros con el mismo nivel de detalle. Seguidamente, otro lenguaje, denominado intent composite description language (ICDL), se apoya en los dos lenguajes anteriores, ofreciendo más flexibilidad para describir algunas partes de la trayectoria y dejar otras sin especificar. El ICDL se usa para proporcionar descripciones genéricas de maniobras comunes, que después se particularizan y combinan para formar descripciones complejas de un vuelo. Otro lenguaje puede construirse a partir del ICDL, denominado flight intent description language (FIDL). El FIDL especifica requisitos de alto nivel sobre las trayectorias —incluyendo restricciones y objetivos—, pero puede utilizar características del ICDL para proporcionar niveles de detalle arbitrarios en las distintas partes de un vuelo. Tanto el ICDL como el FIDL han sido desarrollados en colaboración con Boeing Research & Technology Europe (BR&TE). También se ha desarrollado un lenguaje para definir misiones en las que interactúan varias aeronaves, el mission intent description language (MIDL). Este lenguaje se basa en el FIDL y mantiene todo su poder expresivo, a la vez que proporciona nuevas semánticas para describir tareas, restricciones y objetivos relacionados con la misión. En ATM, los movimientos de un avión en la superficie de aeropuerto también tienen que ser monitorizados y gestionados. Otro lenguaje formal ha sido diseñado con este propósito, llamado surface movement description language (SMDL). Este lenguaje no pertenece a la jerarquía de lenguajes descrita en el párrafo anterior, y se basa en las clearances (autorizaciones del controlador) utilizadas durante las operaciones en superficie de aeropuerto. También proporciona medios para expresar incertidumbre y posibilidad de cambios en las distintas partes de la trayectoria. Finalmente, esta tesis explora las aplicaciones de estos lenguajes a la predicción de trayectorias y a la planificación de misiones. El concepto de trajectory language processing engine (TLPE) se usa en ambas aplicaciones. Un TLPE es una función de ATM cuya principal entrada y salida se expresan en cualquiera de los lenguajes incluidos en la jerarquía descrita en esta tesis. El proceso de predicción de trayectorias puede definirse como una combinación de TLPEs, cada uno de los cuales realiza una pequeña sub-tarea. Se le ha dado especial importancia a uno de estos TLPEs, que se encarga de generar el perfil horizontal, vertical y de configuración de la trayectoria. En particular, esta tesis presenta un método novedoso para la generación del perfil vertical. El proceso de planificar una misión también se puede ver como un TLPE donde la entrada se expresa en MIDL y la salida consiste en cierto número de trayectorias —una por cada aeronave disponible— descritas utilizando FIDL. Se ha formulado este problema utilizando programación entera mixta. Además, dado que encontrar caminos óptimos entre distintos puntos es un problema fundamental en la planificación de misiones, también se propone un algoritmo de búsqueda de caminos. Este algoritmo permite calcular rápidamente caminos cuasi-óptimos que esquivan todos los obstáculos en un entorno urbano. Los diferentes lenguajes formales definidos en esta tesis pueden utilizarse como una especificación estándar para la difusión de información entre distintos actores de la gestión del tráfico aéreo. En conjunto, estos lenguajes permiten describir trayectorias con el nivel de detalle necesario en cada aplicación, y se pueden utilizar para aumentar el nivel de automatización explotando esta información utilizando sistemas de soporte a la toma de decisiones. La aplicación de estos lenguajes a algunas funciones básicas de estos sistemas, como la predicción de trayectorias, han sido analizadas. ABSTRACT Future air traffic management (ATM) will require a paradigm shift from today’s mainly tactical ATM to trajectory-based operations (TBOs). An increase in the level of automation will also relieve humans —air traffic control officers (ATCOs), flight crew, etc.— from many of the tasks they perform today. Humans will still be central in this future ATM, as decision-makers and managers. These two improvements (TBOs and increased automation) are expected to provide the increase in ATM performance that will allow coping with the expected increase in air transport demand. Under TBOs, trajectories are negotiated between the airspace user (an airline, pilot, or operator) and the air navigation service provider (ANSP) using a collaborative decision making (CDM) process. A suitable method for sharing aircraft trajectories is necessary for this negotiation. Sharing a whole trajectory would require a high amount of bandwidth, and the shared trajectory might become invalid if the weather forecast changed. Instead, a description of the trajectory, decoupled from the weather conditions, could be shared, so that the actual trajectory could be computed from this trajectory description. This trajectory description should be easy to process using a computing program —as some of the CDM processes will be automated— but also easy to understand for a human operator —who will be supervising the process and making decisions. This thesis presents a series of formal languages that can be used for this purpose. These languages provide the means to describe aircraft trajectories during all phases of flight, from push back to arrival at the gate. They can also describe trajectories of both manned and unmanned aircraft, including fixedwing and some rotary-wing aircraft (quadrotors). Some of these languages are tightly interrelated and organized in a language hierarchy. One of the key languages in this hierarchy, the aircraft intent description language (AIDL), had already been developed prior to this thesis. This language was derived from the equations of motion of fixed-wing aircraft, and can provide an unambiguous description of fixed-wing aircraft trajectories. A variant of this language, the quadrotor AIDL (QR-AIDL), is developed in this thesis to allow describing a quadrotor aircraft trajectory with the same level of detail. Then, the intent composite description language (ICDL) is built on top of these two languages, providing more flexibility to describe some parts of the trajectory while leaving others unspecified. The ICDL is used to provide generic descriptions of common aircraft manoeuvres, which can be particularized and combined to form complex descriptions of flight. Another language is built on top of the ICDL, the flight intent description language (FIDL). The FIDL specifies high-level requirements on trajectories —including constraints and objectives—, but can use features of the ICDL to provide arbitrary levels of detail in different parts of the flight. The ICDL and FIDL have been developed in collaboration with Boeing Research & Technology Europe (BR&TE). Also, the mission intent description language (MIDL) has been developed to allow describing missions involving multiple aircraft. This language is based on the FIDL and keeps all its expressive power, while it also provides new semantics for describing mission tasks, mission objectives, and constraints involving several aircraft. In ATM, the movement of aircraft while on the airport surface also has to be monitored and managed. Another formal language has been designed for this purpose, denoted surface movement description language (SMDL). This language does not belong to the language hierarchy described above, and it is based on the clearances used in airport surface operations. Means to express uncertainty and mutability of different parts of the trajectory are also provided. Finally, the applications of these languages to trajectory prediction and mission planning are explored in this thesis. The concept of trajectory language processing engine (TLPE) is used in these two applications. A TLPE is an ATM function whose main input and output are expressed in any of the languages in the hierarchy described in this thesis. A modular trajectory predictor is defined as a combination of multiple TLPEs, each of them performing a small subtask. Special attention is given to the TLPE that builds the horizontal, vertical, and configuration profiles of the trajectory. In particular, a novel method for the generation of the vertical profile is presented. The process of planning a mission can also be seen as a TLPE, where the main input is expressed in the MIDL and the output consists of a number of trajectory descriptions —one for each aircraft available in the mission— expressed in the FIDL. A mixed integer linear programming (MILP) formulation for the problem of assigning mission tasks to the available aircraft is provided. In addition, since finding optimal paths between locations is a key problem to mission planning, a novel path finding algorithm is presented. This algorithm can compute near-shortest paths avoiding all obstacles in an urban environment in very short times. The several formal languages described in this thesis can serve as a standard specification to share trajectory information among different actors in ATM. In combination, these languages can describe trajectories with the necessary level of detail for any application, and can be used to increase automation by exploiting this information using decision support tools (DSTs). Their applications to some basic functions of DSTs, such as trajectory prediction, have been analized.