Πολλά είναι τα προβλήματα απόφασης τα οποία μπορούν να μοντελοποιηθούν ως προβλήματα γραμμικού προγραμματισμού. Πολλές όμως είναι και οι καταστάσεις όπου δεν είναι λογικό να υποτεθεί ότι οι παράμετροι του μοντέλου καθορίζονται προσδιοριστικά. Για παράδειγμα, μελλοντικές παραγωγικότητες σε ένα πρόβλημα παραγωγής, εισροές σε μία δεξαμενή που συνδέεται με έναν υδροσταθμό παραγωγής ηλεκτρικού ρεύματος, απαιτήσεις στους διάφορους κόμβους σε ένα δίκτυο μεταφορών κλπ, είναι καταλληλότερα μοντελοποιημένες ως αβέβαιες παράμετροι, οι οποίες χαρακτηρίζονται στην καλύτερη περίπτωση από τις κατανομές πιθανότητας. Η αβεβαιότητα γύρω από τις πραγματοποιημένες τιμές εκείνων των παραμέτρων δεν μπορεί να εξαλειφθεί πάντα εξαιτίας της εισαγωγής των μέσων τιμών τους ή μερικών άλλων (σταθερών) εκτιμήσεων κατά τη διάρκεια της διαδικασίας μοντελοποίησης. Δηλαδή ανάλογα με την υπό μελέτη κατάσταση, το γραμμικό προσδιοριστικό μοντέλο μπορεί να μην είναι το κατάλληλο μοντέλο για την περιγραφή του προβλήματος που θέλουμε να λύσουμε. Σε αυτή τη διπλωματική υπογραμμίζουμε την ανάγκη να διευρυνθεί το πεδίο της μοντελοποίησης των προβλημάτων απόφασης που παρουσιάζονται στην πραγματική ζωή με την εισαγωγή του στοχαστικού προγραμματισμού. / There are many practical decision problems than can be modeled as linear programs. However, there are also many situations that it is unreasonable to assume that the coefficients of model are deterministically fixed. For instance, future productivities in a production problem, inflows into a reservoir connected to a hydro power station, demands at various nodes in a transportation network, and so on, are often appropriately modeled as uncertain parameters, which are at best characterized by probability distributions. The uncertainty about the realized values of those parameters cannot always be wiped out just by inserting their mean values or some other (fixed) estimates during the modelling process. That is, depending on the practical situation under consideration, the linear deterministic model may not be the appropriate model for describing the problem we want to solve. In this project we emphasize the need to broaden the scope of modelling real life decision problems by inserting stochastic programming.

Dans cette thèse, nous considérons le problème du séquencement sur une ligne de montage multi-modèles de véhicules industriels. Pour équilibrer au mieux la charge dynamique des opérateurs, la minimisation de la somme des retards à l’issue de chaque véhicule est proposée.Deux approches peuvent être utilisées pour optimiser le lissage de charge dans un problème de séquencement : l’utilisation directe des temps opératoires ou le respect de règles. La plupart des travaux appliqués à l’industrie automobile utilisent l’approche de respect de règles. Une originalité de ce travail est d’utiliser l’approche de la prise en compte directe des temps opératoires.L’étude de la littérature de ce problème a dévoilé deux lacunes dans les travaux précédents : l’essentiel des travaux modélisent un seul type d’opérateurs d’une part, et proposent des heuristiques ou des métaheuristiques pour résoudre ces problèmes, d’autre part. L’originalité de ce travail est de tester des méthodes exactes pour des instances industrielles et de modéliser le fonctionnement de trois différents types d’opérateurs spécifiques au cas industriel.Deux méthodes exactes sont développées : la programmation linéaire mixte et la programmation dynamique. Une étude expérimentale des facteurs de complexité sur des instances académiques des deux modèles est développée. Les modèles sont aussi testés sur des instances du cas d’étude.Par ailleurs, le problème est traité par deux méthodes approchées : une heuristique basée sur la programmation dynamique d’une part, et des métaheuristiques (algorithme génétique, recuit simulé et un couplage des deux) d’autre part. Les deux approches sont testées sur des instances académiques et des instances du cas d’étude.Ce travail a permis d’apporter une solution intéressante d’un point de vue industriel puisqu’il prend en compte les caractéristiques de la ligne de montage (opérateurs spécifiques) et améliore significativement la qualité du séquencement en un temps de calcul raisonnable. / In this thesis, the problem of sequencing mixed model assembly lines (MMAL) is considered. Our goal is to determine the sequence of products to minimize the work overload. This problem is known as the mixed model assembly line sequencing problem with work overload minimization (MMSP-W). This work is based on an industrial case study of a truck assembly line.Two approaches can be used to minimize the work overload: the use of task operation times or the respect of sequencing rules. Most of the earlier works applied in car industry use the latter approach. The originality of this work is to employ the task operation times for the generation of the product sequence in a MMAL.The literature review has highlighted two main gaps in previous works: most of the papers consider a single type of operators, and propose heuristics or metaheuristics to solve the problem. The originality of this work is to test exact methods for industrial case instances and to model three different types of operators.Two exact methods are developed: the mixed integer linear programming and dynamic programming. The models are tested on industrial case study instances. An experimental study is developed for both approaches in order to understand the complexity factors.Moreover, the problem is treated by two approximate methods: a heuristic based on dynamic programming and metaheuristics (genetic algorithm, simulated annealing and a hybrid method based on both genetic algorithm and simulated annealing). All approaches are tested on academic instances and on real data from the industrial case study.

Les travaux de cette thèse s’articulent autour des « problèmes d’ordonnancement multiagent avec une fonction objectif globale ». Ces modèles considèrent différents agents associés à des sous-ensembles de travaux disjoints, chacun d’eux vise à minimiser un objectif qui ne dépend que de ses propres travaux. Un critère global est aussi considéré, qui est appliqué à la totalité des travaux. La résolution de ces problèmes revient à trouver les meilleurs compromis entre les critères des agents et le critère global. Ces problèmes sont une classe particulière des problèmes d’ordonnancement « multi-agents » qui ont connu une grande expansion, reflétant leurs intérêts dans le domaine de l’ordonnancement. / This thesis addresses the multi-agent scheduling problems with a global objective function. We consider the problems featured by various agents, each of which is associated with a distinct subset of jobs. Each agent aims at minimizing a certain objective function, which only operates on its assigned jobs. A global criterion associated with a global agent is applied on the whole set of the jobs. Solving these problems involves finding the best compromises between the requirements of agents and that of the global agent. These problems belong to a particular class of multi-criteria scheduling problems. Such a class has drawn a significant interest to researchers in the area of scheduling and operational research.

Dans les véhicules hybrides électrique-essence, les stratégies de gestion de l’énergie déterminent la répartition des flux d'énergies des moteurs thermique et électrique avec pour objectif classique la réduction de la consommation. Par ailleurs, pour respecter les seuils réglementaires d’émissions polluantes, les motorisations essence sont équipées d’un catalyseur 3-voies chauffé par les gaz d’échappement. Une fois amorcé, ce catalyseur convertit presque entièrement les émissions polluantes du moteur. C’est donc au démarrage que la plupart de la pollution est émise, lorsque le catalyseur est froid et que la pollution du moteur n’est pas convertie. La chauffe du catalyseur est donc l’étape clé de la dépollution. Ce mémoire propose une démarche de prise en compte des émissions polluantes par la gestion d’énergie. Le véhicule hybride est assimilé à un système dynamique à deux états, l’état de charge batterie et la température du catalyseur. Un problème d’optimisation dynamique est défini, qui minimise un critère original pondérant judicieusement la consommation et les émissions polluantes. La théorie de la commande optimale, avec les Principes du Minimum de Pontryaguine et de Bellman, permet de résoudre ce problème d’optimisation. Des stratégies optimales sont déduites et simulées avec un modèle de véhicule intégrant un modèle thermique multi-zones de catalyseur, validé expérimentalement, qui simule précisément la chauffe. Le compromis entre la consommation et la pollution est exploré. Une stratégie de chauffe du catalyseur, plus méthodique, analytique et efficace que les stratégies empiriques actuelles, est alors proposée. Cette stratégie est validée expérimentalement dans un environnement HyHIL (Hybrid Hardware In the loop). Une importante réduction de la pollution est obtenue, confortant l’approche d’optimisation dynamique pour la mise au point des stratégies de gestion d’énergie du véhicule hybride. / In hybrid gasoline-electric vehicles, the energy management strategies determine the distribution of engine and motor energy flows with fuel consumption reduction as classical objective. Furthermore, to comply with pollutant emissions standards, SI engines are equipped with 3-Way Catalytic Converters (3WCC) heated by exhaust gases. When 3WCC temperature is over the light-off temperature, engine pollutant emissions are almost totally converted. Most of the pollution is produced at the vehicle start, when the 3WCC is cold and the engine pollution is not converted. The 3WCC heating is thus the key aspect of the pollutant emissions. This dissertation proposes an approach to take into account pollutant emissions in energy management. The hybrid electric vehicle is considered as a dynamic system with two states, the battery state of charge and 3WCC temperature. A dynamic optimization problem is defined, minimizing an original criterion weighting judiciously fuel consumption and pollutant emissions. Optimal control theory, with the Pontryaguine Minimum and Bellman principles, allows solving this optimization problem. Optimal strategies are derived and simulated with a vehicle model including a multi-zones 3WCC thermal model, experimentally validated, which simulates precisely the 3WCC heating. The compromise between fuel consumption and pollutant emissions is explored. Then, an innovative 3WCC heating strategy is proposed and validated experimentally in a HyHIL (Hybrid Hardware In the loop) environment. A significant reduction of the pollutant emissions is obtained, strengthening the dynamic optimal approach to set up the energy management strategies for hybrid vehicles.

Le véhicule hybride électrique dispose de deux sources d’énergie distinctes pour se mouvoir : le carburant, ainsi qu’un système de stockage électrique ayant la particularité d’être réversible. La loi de gestion d’énergie a pour objectif de superviser les flux de puissance dans le groupe motopropulseur en intervenant sur le point de fonctionnement des organes de celui-ci, et ce dans le but d’optimiser un critère donné. La loi de gestion d’énergie se formalise donc par un problème de commande optimale dont le critère à minimiser tient compte de la consommation de carburant du véhicule sur un trajet donné. La solution de ce problème peut se calculer hors ligne lorsque toutes les données du trajet sont parfaitement connues à l’avance, hypothèse qui n’est plus admissible pour une stratégie embarquée sur véhicule dont l’objectif est alors de s’approcher au maximum du résultat optimal. Les travaux présentés dans ce manuscrit mettent en avant la commande optimale orientée multi-objectif pour répondre à la problématique du compromis inter-prestations au coeur du développement d’un véhicule de série. Une loi de gestion d’énergie tenant compte du compromis entre consommation et agrément de conduite, ainsi qu’une autre traitant le compromis entre consommation et vieillissement batterie sont proposées. Les stratégies présentées s’inscrivent également dans une approche modulaire tirée de la solution de nature transversale issue de l’Equivalent Consumption Minimization strategy (ECMS). Ainsi, la commande du véhicule hybride rechargeable, du Mild-Hybride, ainsi que d’architectures hybrides complexes disposant d’une transmission automatique, de deux machines électriques ou deux systèmes de stockage électriques, est ici traitée à travers un socle commun. Cette approche permet de réduire le temps de développement des stratégies qui partagent un maximum d’éléments communs. / The hybrid electric vehicle uses two different energy sources to propel itself: fuel as well as a reversible electric storage system. The energy management strategy aims at supervising the power flows inside the powertrain by choosing the operating points of the different components so as to optimize a given criterion. The energy management strategy is formulated as an optimal control problem where the criterion to be minimized takes into account the total fuel consumption of the vehicle on the considered trip. The optimal solution can be calculated off-line when the vehicle’s mission is perfectly known, an assumption no longer admissible for an embedded strategy whose main objective is to get as close as possible to the optimal result. The work presented in this manuscript highlights the potential of multi-objective optimal control to handle the features’ trade-offs inherent to the development of production vehicle. An energy management strategy taking into account the trade-off between fuel consumption and drivability, as well as one dealing with the trade-off between fuel consumption and battery state of health, are proposed. The presented strategies share a modular approach following the transversal solution of the Equivalent Consumption Minimization Strategy (ECMS). As a result, the control policy of the plug-in hybrid electric vehicle, the Mild-Hybrid, together with complex hybrid architectures provided with an automated transmission, two electric machines or two electric storage systems, is tackled through a common base. This approach allows to reduce the development period of the energy management strategies which shares a maximum of common elements.

This dissertation investigates high-level decision making for agents that are both goal and utility driven. We develop a partially observable Markov decision process (POMDP) planner which is an extension of an agent programming language called DTGolog, itself an extension of the Golog language. Golog is based on a logic for reasoning about action—the situation calculus. A POMDP planner on its own cannot cope well with dynamically changing environments and complicated goals. This is exactly a strength of the belief-desire-intention (BDI) model: BDI theory has been developed to design agents that can select goals intelligently, dynamically abandon and adopt new goals, and yet commit to intentions for achieving goals. The contribution of this research is twofold: (1) developing a relational POMDP planner for cognitive robotics, (2) specifying a preliminary BDI architecture that can deal with stochasticity in action and perception, by employing the planner. / Computing / M. Sc. (Computer Science)

Orientador: Edvaldo Assunção / Resumo: Neste trabalho estudamos problemas de controle ótimo intervalar e intervalar fuzzy. Em particular, propomos problemas de controle ótimo via teoria de incerteza generalizada e teoria dos conjuntos fuzzy. Dentre os vários tipos de incerteza generalizada utilizamos apenas a intervalar. Embora as abordagens do processo de solução dos problemas de controle ótimo intervalar e intervalar fuzzy sejam similares, as premissas iniciais para o uso e identificação de aplicação delas em problemas práticos são distintas assim como é distinto o processo de tomada de decisão. Assim, propomos inicialmente o problema de controle ótimo intervalar em tempo discreto. A primeira proposta de solução para o problema de controle ótimo intervalar em tempo discreto é construída usando a aritmética intervalar restrita de níveis simples juntamente com a técnica de programação dinâmica. As respostas do problema de controle ótimo intervalar contêm as possibilidades de soluções viáveis, e para implementar uma solução viável para o usuário final usamos a solução que minimiza o arrependimento máximo nos exemplos numéricos. A segunda proposta de solução para o problema de controle ótimo intervalar em tempo discreto é realizada com a aritmética intervalar restrita uma vez que essa aritmética intervalar é mais geral do que a aritmética intervalar restrita de níveis simples pois não considera os intervalos envolvidos nas operações variando de forma dependente. Exemplos numéricos também foram construídos e ilustram... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: In this work we study the interval optimal control problem and fuzzy interval optimal control problem. In particular, we propose optimal control problems via theory of generalized uncertainty and fuzzy set theory. Among the various types of generalized uncertainty we use only the interval uncertainty. Although the approaches to solve the interval optimal control problem and fuzzy interval optimal control problem are similar, the input data for problems with generalized uncertainty and flexibility are distinct as is distinct the decision-making process. Thus, we initially propose the discrete-time interval optimal control problem. The first solution method to solve the discrete-time interval optimal control problem is constructed using single-level constrained interval arithmetic coupled with a dynamic programming technique. The optimal interval solution contains the real-valued optimal solutions, and to implement a feasible solution to the user we use the minimax regret criterion in numerical examples. The second solution method to solve the discrete-time interval optimal control problem is done with the constrained interval arithmetic since this interval arithmetic is more general than the single-level constrained interval arithmetic because it does not have its intervals varying of dependent form in interval operations. Numerical examples have also been constructed and illustrate the method of solution. Finally, we study the discrete-time fuzzy interval optimal control prob... (Complete abstract click electronic access below) / Doutor

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/Thesis / Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2018

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Made available in DSpace on 2016-08-17T14:53:16Z (GMT). No. of bitstreams: 1 Leandro Rocha Lopes.pdf: 1075564 bytes, checksum: 01e184ed6d7c65323c0dfc1515da19a3 (MD5) Previous issue date: 2011-04-04 / Due to the increasing of technological development and its associated industrial applications, control design methods to attend high performance requests and reinforcement learning are been developed, not only, to solve new problems, as well as, to improve the performance of implemented controllers in the real systems. The reinforcement learning (RL) and discrete linear quadratic regulator (DLQR) approaches are connected by adaptive dynamic programming (ADP). This connection is oriented to the design of optimal controller for multivariable systems (MIMO). The proposed method for DLQR controllers tuning can been heuristic guidance for biased variations in weighting matrices of instantenous reward. The heuristics performance are evaluated in terms of convergence of heuristic dynamic programming (HDP) and action dependent (AD-HDP) algorithms. The algorithms and tuning are evaluated by the capability to map the plane-Z in MIMO dynamic system of third order. / Em decorrência do crescente desenvolvimento tecnológico e das consequentes aplicações industriais, técnicas de controle de alto desempenho e aprendizado por reforço estão sendo desenvolvidas não só para solucionar novos problemas, mas também para melhorar o desempenho de controladores já implementados em sistemas do mundo real. As abordagens do aprendizado por reforço e do regulador linear quadrático discreto (DLQR) são conectadas pelos métodos de programação dinâmica adaptativa. Esta união é orientada para o projeto de controladores ótimos em sistemas multivariáveis (MIMO). O método proposto para sintonia de controladores DLQR fornece diretrizes para construção de heurísticas polarizadas que são aplicadas na seleção das matrizes de ponderação da recompensa instantânea. Investiga-se o desempenho das heurísticas associadas com a sintonia de controladores lineares discretos e aspectos de convergência que estão relacionados com as variações QR nos algoritmos de programação dinâmica heurística (HDP) e Ação Dependente (ADHDP). Os algoritmos e a sintonia são avaliados pela capacidade em estabelecer a política de controle ótimo que mapeia o plano-Z em um sistema dinãmico multivariável de terceira ordem.