L'hybridation des mécanismes de méthodes incomplètes et des techniques de programmation par contraintes est souvent basée sur des combinaisons de type maître-esclave, dédiées à la résolution de classes de problèmes spécifiques. Dans cette thèse, nous nous intéressons à la définition d'un modèle théorique uniforme, basé sur les itérations chaotiques de K.R. Apt qui définissent un cadre mathématique pour l'itération d'un ensemble fini de fonctions sur des domaines abstraits munis d'un ordre partiel. Ce cadre permet<br />de prendre en compte une hybridation entre les méthodes incomplètes et les méthodes complètes. Dans ce contexte, la résolution s'apparente à un calcul de point fixe d'un ensemble de fonctions de réductions spécifiques. Notre cadre générique permet alors d'envisager des stratégies de combinaisons et d'hybridation de manière plus fine et d'étudier leurs propriétés. Nous avons employé un cadre général approprié pour modéliser la résolution des problèmes d'optimisation et nous présentons des résultats<br />expérimentaux qui mettent en avant les atouts de telles<br />combinaisons en regard d'une utilisation indépendante des techniques de résolution.

La fréquence d'opération des circuits intégrés continue<br />de monter donc l'inductance des interconnexions devient non<br />négligeable. Il est donc nécessaire de pouvoir la calculer de<br />façon précise pour une analyse à posteriori correcte. Dans cette<br />thèse, nous développons une nouvelle approche pour<br />le calcul de l'impédance propre et mutuelle dans les<br />interconnexions. Notre méthode alternative est moins chère, du<br />point vu du calcul, que celle du PEEC. Elle est aussi plus stable mais<br />tout de même aussi précise. Nous résoudrons le problème<br />de capturer la dépendance en fréquence de l'impédance,<br />conséquence des effets de proximité et de peau.<br /><br />Nous étendons notre analyse a l'étude de l'impédance propre<br />et mutuelle des dispositifs passifs, plus spécifiquement les<br />inducteurs intentionnels. Nous incluons un modèle RLC utile pour<br />capturer des informations importantes comme la fréquence de<br />résonance ou le facteur de qualité.<br /><br />Nous dérivons une expression originale pour le délai d'une ligne<br />de transmission RLC excitée par une rampe avec un temps de<br />montée non nul et avec une capacité de charge placée à la fin<br />de la ligne.<br /><br />Nous présentons une application utile des effets inductifs dans les<br />circuits intégrés. Ce que nous montrons est la faisabilité<br />pour transmettre des signaux à la vitesse maximale, celle de la<br />lumière dans le milieu de transmission.

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This thesis explores a border security system based on agent-based modeling and simulation (ABMS). The ABMS software platform, map aware non-uniform automata, is used to model various scenarios and evaluate the border security system given a set of infiltrators who have evolutionary behavior governed by a genetic algorithm (GA). The GA is used to represent adaptive behavior of the enemy when the friendly force has deployed our border security at a maximum level. By using a near optimal Latin hypercube design, our simulation runs are implemented efficiently and the border security system is analyzed using four different kinds of measures of effectiveness. / text

Traffic congestion has been placing an extremely high burden on the development of modern cities. Congestion can be alleviated by either increasing road capacity, or by reducing traffic demand. For decades, increasing capacity by building more roads and lanes has been the major solution applied to accommodate the ever-growing traffic demand. However, it turns out to be of limited effect due to some well-known phenomenon such as latent demand. Controlling and managing traffic demand has in turn been viewed as a cost-effective alternative to increasing road capacity, as has been demonstrated many successful applications all around the world. Within the concept framework of Traffic Demand Management (TDM), Active Transportation and Demand Management (ATDM) is the dynamic management, control, and influence of traffic demand and traffic flow of transportation facilities. ATDM strategies attempt to influence traveler behavior and further manage traffic flow in a time-dependent manner within the existing infrastructure Successful ATDM applications include congestion pricing, adaptive ramp metering, dynamic speed limits, dynamic lane use control, etc. Singapore stands out to be an excellent success story of ATDM, as the implementations of "Cap and Trade" license plates and electronic road pricing make motoring a high cost privilege for citizens of Singapore, making the public relies on transit. Monetary leverage is an effective instrument to facilitate ATDM. Examples of ATDM applications adopting monetary instrument includes dynamic congestion pricing, "Cap and Trade" of car licenses, etc. Taking congestion pricing as an example, policy makers are inducing travelers' behavior and alternating their preferences towards different behavior decisions by levying price tags to different choices. As an important underpinning of rationing choice theory, an individual assigns an ordinal number over the available actions and this ordinal number is calculated by their utility function or payoff function. The individual's preference is expressed as the relationship between those ordinal assignments. In the implementation of congestion pricing, policy makers are imposing an additional high disutility to congested roads and therefore pushing some of the travelers to take alternative routes or shift to alternative departure times or even cancel the trips. However, congestion pricing suffers from public aversion as it creates burden on the motoring of low-income people and therefore doesn't help to alleviate social inequality. The concept of Tradable Mobility Credit (TMC) has been proposed by a group of researchers as another innovative application to facilitate dynamic traffic demand management and solve social inequality issues using pricing instruments. The concept of TMC is borrowed from carbon trading in environmental control. A limited quota of personal auto usage is issued to eligible travelers and credits can be traded in a free market fashion. This guarantees that the roadway usage does not exceed capacity while avoiding the negative effects of shortages normally associated with quotation systems. TMC is literally not a market-ready policy as the integration of the supporting infrastructures, including the trading market, the credit assignment component, and the credit charging component, has not been fully explored yet. Existing TMC research focuses on explaining and exploring the equilibrium condition through analytical methods such as mathematical modeling. Analytical models produce perfect convergence curves and deterministic equilibrium traffic flow patterns. Analytical models provide influential guidance for further works but the solution procedure may encounter problems when dealing with larger real world networks and scenarios. Meantime, current analytical models don't consider the microstructure of the credit trading market sufficiently while it's actually the most unique component of TMC system. Motivated by those concerns, an integrated TMC evaluation platform consisting of a policy making module and traveler behavior modules are proposed in this research. The concept of Agent-Based Modeling and Simulation (ABMS) is extensively adopted in this integrated platform as each individual traveler carries his/her personal memory across iterations. The goal of establishing this framework is to better predict a traveler's route choice and trading behavior if TMC is imposed and further provide intelligence to potential policy makers' decision making process. The proposed integrated platform is able to generate results at different aggregation levels, including both individual level microscopic behavior data as well as aggregated traffic flow and market performance data. In order to calibrate the proposed integrated platform, an online interactive experiment is designed based on an experimental economic package and a human research element with 22 participants has been conducted on this experiment platform to gather field data regarding a real person's route choice behavior and credit trading behavior in an artificial TMC system. Participants are recruited from forum, listserve, social media, etc. The calibrated platform is proved to have the ability to predict travelers' behavior accurately. A prototype market microstructure is proposed in this research as well and it is proved to be a cost-effective setting and resulted to a vast amount of economic saving given the fact that travelers would behave similar to the prediction generated by traveler behavior module. It's also demonstrated that the principle of Pareto-improving is not achieved in the proposed ABMS models.

Interoperability between heterogeneous software systems is an important issue to increase software reusability in the software industry. Many methods are proposed to implement interoperable systems using distributed computing infrastructures such as CORBA, HLA and SOA. Those infrastructures can provide communication channels between software systems with heterogeneous environments. SOA (Service Oriented Architecture) provides a more flexible approach to interoperability than do the others because it provides platform independence and employs platform-neutral message passing with Simple Object Access Protocol (SOAP) to communicate between a service and a client.The main contribution of this study is to design and implement an interoperable DEVS simulation environment using the SOA concept and a new construct called the DEVS namespace. The interoperable DEVS environment consists of a DEVS simulator service and an associated integrator. The DEVS simulator service provides both simulator level and model level interoperability. Moreover, using the DEVS namespace, DEVS simulator services can be interoperable with any services using the same message types.To demonstrate the utility of the proposed environment, we describe various applications of the interoperable DEVS simulation environment. The applications are drawn from real world development of automated testing environments for military information system interoperability. A radar track generation and display federation and a model negotiation web service illustrated the ability of the proposed middleware to work across platforms and languages. Its ability to support higher level semantic interoperability will be demonstrated in a testing service that can deploy model agents to provide coordinated observation of web requests of participants in simulated distributed scenarios.

Le contexte industriel indissociable de l'évolution des Technologies de l'Information et de la Communication donne naissance aujourd'hui à de nouvelles formes d'organisations fortement basées sur les collaborations inter-entreprises. Dans ce contexte de réseaux collaboratifs, la qualité de l'émergence de nouveaux partenariats dépend largement des dispositifs de traitement et de partage de l'information. La recherche d'information pertinentes caractérisant les entreprises devient un outil indispensable aux managers et aux divers acteurs économiques, en vue de détecter des liens de collaboration potentiels. Dans le cadre de ces travaux de thèse, nous avons ciblé la complémentarité des activités et la similarité des compétences comme informations clés destinées à analyser les opportunités d'émergences de collaborations inter-entreprises. Ce travail de recherche s'inscrit dans le cadre de la mise en oeuvre de systèmes de recherche et d'extraction automatique d'information à partir du web (site web des entreprises). L'objectif est de répondre aux besoins d'un environnement informationnel ouvert, concernant les entreprises. La thèse vise à développer des mécanismes ciblés d'extraction d'information, dont l'utilisation sera préalable à l'application d'outil d'aide à la décision dans le domaine des collaborations inter-entreprises. La contribution est basée sur une représentation sémantique de l'information en se basant sur les ontologies, les liens sémantiques et un traitement linguistique articulé sur l'utilisation des patrons syntaxiques. Deux mécanismes d'extraction d'information sont mis en place, l'un orienté sur l'identification des secteurs d'activités des entreprises et l'autre sur le repérage de leurs compétences.

Le travail présenté dans cette thèse concerne l'application des techniques de l'automatique au domaine automobile. Nous avons abordé plus particulièrement les problèmes de modélisation et de commande. Le travail est organisé en deux parties : la première est dédiée à un certain nombre d'aspects de modélisation. Une telle modélisation peut être effectuée en différents sous-ensembles et/ou représentée par des modèles plus ou moins compliqués. Les indicateurs plus souvent employés dans la littérature pour évaluer le comportement dynamique des véhicules, en terme de performance, tenue de route et confort sont analysés. La deuxième partie de la thèse met en évidence quelques problèmes de commande intéressants pour améliorer le comportement dynamiques des véhicules. Nous présentons ensuite, en vue de l'application au véhicule, une méthodologie de commande robuste et/ou adaptative développée au laboratoire d'automatique de Grenoble. Cette méthodologie est ensuite appliquée au problème de conduite automatique de véhicule, ou seul l'écart latéral, véhicule-trajectoire, est utilisé comme retour d'information. Pour simuler le comportement du véhicule, un modèle complet non linéaire est utilisé.

This research proposes an efficient reliability modeling and simulation methodology in power systems to include photovoltaic units, wind farms and storage. Energy losses by wake effect in a wind farm are incorporated. Using the wake model, wind shade, shear effect and wind direction are also reflected. For solar modules with titled surface, more accurate hourly photovoltaic power in a specific location is calculated with the physical specifications. There exists a certain level of correlation between renewable energy and load. This work uses clustering algorithms to consider those correlated variables. Different approaches are presented and applied to the composite power system, and compared with different scenarios using reliability analysis and simulation. To verify the results, reliability indices are compared with those from original data. As the penetration of renewables increases, the reliability issues will become more important because of the intermittent and non-dispatchable nature of these sources of power. Storage can provide the ability to regulate these fluctuations. The use of storage is investigated in this research. To determine the operating states and transition times of all turbines, Monte Carlo is used for system simulation in the thesis. A conventional power system from IEEE Reliability Test Systems is used with transmission line capacity, and wind and solar data are from National Climatic Data Center and National Renewal Energy Laboratory. The results show that the proposed technique is effective and efficient in practical applications for reliability analysis.

No description available.