Image segmentation is an important research area in digital image processing with several applications in vision-guided autonomous robotics, product quality inspection, medical diagnosis, the analysis of remotely sensed images, etc. The aim of image segmentation can be defined as partitioning an image into homogeneous regions in terms of the features of pixels extracted from the image. Image segmentation methods can be classified into four main categories: 1) clustering methods, 2) region-based methods, 3) hybrid methods, and 4) bayesian methods. In this thesis, major image segmentation methods belonging to first three categories are examined and tested on typical images. Moreover, improvements are also proposed to well-known Recursive Shortest-Spanning Tree (RSST) algorithm. The improvements aim to better model each region during merging stage. Namely, grayscale histogram, joint histogram and homogeneous texture are used for better region modeling.

In this thesis, we use integer programming techniques to solve the resource constrained shortest path problem (RCSPP) which seeks a minimum cost path between two nodes in a directed graph subject to a finite set of resource constraints. Although NP-hard, the RCSPP is extremely useful in practice and often appears as a subproblem in many decomposition schemes for difficult optimization problems. We begin with a study of the RCSPP polytope for the single resource case and obtain several new valid inequality classes. Separation routines are provided, along with a polynomial time algorithm for constructing an auxiliary conflict graph which can be used to separate well known valid inequalities for the node packing polytope. We establish some facet defining conditions when the underlying graph is acyclic and develop a polynomial time sequential lifting algorithm which can be used to strengthen one of the inequality classes. Next, we outline a branch-and-cut algorithm for the RCSPP. We present preprocessing techniques and branching schemes which lead to strengthened linear programming relaxations and balanced search trees, and the majority of the new inequality classes are generalized to consider multiple resources. We describe a primal heuristic scheme that uses fractional solutions, along with the current incumbent, to search for new feasible solutions throughout the branch-and-bound tree. A computational study is conducted to evaluate several implementation choices, and the results demonstrate that our algorithm outperforms the default branch-and-cut algorithm of a leading integer programming software package. Finally, we consider the dial-a-flight problem (DAFP), a new vehicle routing problem that arises in the context of on-demand air transportation and is concerned with the scheduling of a set of travel requests for a single day of operations. The DAFP can be formulated as an integer multicommodity network flow model consisting of several RCSPPs linked together by set partitioning constraints which guarantee that all travel requests are satisfied. Therefore, we extend our branch-and-cut algorithm for the RCSPP to solve the DAFP. Computational experiments with practical instances provided by the DayJet Corporation verify that the extended algorithm also outperforms the default branch-and-cut algorithm of a leading integer programming software package.

Diploma thesis named "Geoinformation system for the visually handicapped" deals with design and creation geoinformation system that should serve to visually handicapped people with planing the most appropriate route and their movement in a city. First part of thesis is a brief summary of who are visually handicapped people, their needs, abilities and principles of movement. Further are described barrier-free adaptations for visually handicapped people and existing solutions. Practical output is the design of an algorithm for automatically locating and evaluating critical locations based on OpenStreetMaps solution. Visually handicapped people choose not shortest route, but the safest route for their movement. Key words: Critical Point, Visual Handicap, Shortest Route, Optimization, Routing

L’utilisation des réseaux de transport est conditionnée par l’efficacité et la simplicité de leur utilisation. En réponse à une mobilité exacerbée, volontaire ou subie, l’offre de transport se développe et motive tout à la fois, en un cycle continu, des déplacements encore plus exigeants. De manière complémentaire, la mobilité est bousculée par l’arrivée de nouvelles modalités de transport pouvant faire émerger, comme dans le cadre du covoiturage, des acteurs ou des pratiques jusqu’alors inexistants. Si la technologie permet de suivre cette évolution dans les services d’information aux voyageurs, il reste toujours à satisfaire des attentes déterminées par des usages en constante évolution. C’est de ce point de vue que l’obtention de chemins multiples pour relier une origine à une destination est un facteur qui n’est plus à négliger, surtout dans des réseaux de transport denses et comportant de nombreux modes et lignes de transport. Une liberté dans le choix laissé à l’utilisateur du réseau réduit les sentiments d’exclusion, d’incompréhension ou d’anxiété qui peuvent survenir face à une application logicielle ou sur internet et qui effectuent des choix arbitraires de façon autoritaire. De plus, cela permet de vérifier la qualité de l’offre de transport, car plus il existe de moyens différents pour effectuer un trajet dans un intervalle de temps donné, meilleur est le service. Cette thèse s’intéresse au calcul de telles alternatives par le biais de l’énumération par coût croissant des chemins entre deux points, puis par le filtrage de ceux-ci suivant des critères, supposés quelconques et laissés à l’appréciation des professionnels de transport qui peuvent ainsi faire varier les angles d’analyses de leurs offres.Par ailleurs, la synchronisation de trajets de plusieurs utilisateurs, en vue d’usages sociaux ou de déplacements mutualisés, est étudiée dans ce manuscrit sous l’angle du covoiturage. En ne considérant que deux usagers, l’objectif est de minimiser le temps de trajet global des participants sous la contrainte qu’ils partagent une partie de leur chemin entre un point de rencontre et un point de séparation qu’il faut alors déterminer. Sont également étudiées les variantes associées au changement des conditions de transport de chacun des participants comme l’établissement d’une origine ou d’une destination commune parallèlement à des contraintes sur les heures de départ ou d’arrivée des usagers. Enfin, puisque la voiture est très souvent pénalisée par la prise en charge d’un piéton, il convient d’étudier comment ce détour peut être contraint et les impacts sur les gains que cette limitation engendre.Cette thèse a été réalisée dans un contexte CIFRE pour la société MobiGIS. Lestravaux qui s’y rapportent ont fait l’objet de réalisations pratiques tant pour fournirdes solutions de mobilité dans le cadre des activités de l’entreprise que pour évaluerexpérimentalement les performances des algorithmes proposés pour les résoudre. / Efficiency and simplicity are two conditions upon which the use of a transportation system is relevant. May it be intentional or imposed, an increasing mobility triggers the need to enhance the transportation offer. In turn, such a response encourages an even more demanding mobility in a constantly adapting cycle. In parallel, new and forthcoming means of transportation emerge from time to time with unknown practices and renewed actors : exactly like what carpooling is stirring at the moment. Passenger information systems can technically deal with such evolutions thanks to improved technologies but they still struggle to keep up with constantly changing usage expectations.From this perspective the computation of several paths from an origin to a destination becomes increasingly relevant. This issue is even more crucial in dense transportation networks in which many modes and lines of transportation are combined. Indeed, giving some traveling choices to the end user reduces the feeling of exclusion, anxiety and the lack of understanding which may arise when facing arbitrary decisions dictated by a software or an Internet application. It is also helpful to estimate the quality of the transportation offer since the more paths exist to go from point A to point B within a fixed time window, the better the service is. This thesis focuses on the computation of such alternatives by the gradually increasing enumeration of paths between two points. Given this input, the pruning necessary to obtain such a diverse selection is assumed not to be known in advance. It is left up to transportation professionals who may choose a fitted solution based on their specific knowledge and objectives.Another subject studied in this thesis concerns the itinerary synchronization of several users for various social uses such as shared travels. It is here seen from the perspective of carpooling. Considering only two users, the problem is to minimize the traveling cost of the users under the constraint that they must share some part of their respective trips with one another. Solving this problem is equivalent to finding a pick up point and a drop off location between which both paths overlap. Multiple corner cases concerning the transportation conditions of each user as well as the special cases of shared origins or destinations are studied. The constraints on the arrival and/or departure times may also vary. Last but not least and since the driver is often penalized when giving up a lift, the restriction to a maximal detour the driver accepts, compared to his shortest path, is analyzed with respect to the benefits such a limitation generates.This thesis was funded by the MobiGIS company under the CIFRE (Industrial Agreement of Training through Research) researching context. The related work consisted in the practical implementation of mobility solutions within the framework of the company as well as the experimental performances evaluation of the algorithms proposed to solve them.

This thesis examines some of the best known algorithms for solving the shortest point-to-point path problem, and evaluates their performance on real metropolitan area networks. The focus has mainly been on Dijkstra‟s algorithm and different variations of it, and the algorithms have been implemented in C# for the practical tests. The size of the networks used in this study varied between 358 and 2464 nodes, and both running time and representative operation counts were measured. The results show that many different factors besides the network size affect the running time of an algorithm, such as arc-to-node ratio, path length and network structure. The queue implementation of Dijkstra‟s algorithm showed the worst performance and suffered heavily when the problem size increased. Two techniques for increasing the performance were examined: optimizing the management of labelled nodes and reducing the search space. A bidirectional Dijkstra‟s algorithm using a binary heap to store temporarily labelled nodes combines both of these techniques, and it was the algorithm that performed best of all the tested algorithms in the practical tests. This project was initiated by Netadmin Systems i Sverige AB who needed a new path finding module for their network management system NETadmin. While this study is primarily of interest for researchers dealing with path finding problems in computer networks, it may also be useful in evaluations of path finding algorithms for road networks since the two networks share some common characteristics.

Dans cette thèse, nous étudions plusieurs modèles de routage efficaces en énergie. Pour chaque modèle, nous présentons une formulation en programmation linéaire mixte permettant de trouver une solution exacte. En outre, comme il s’agit de problèmes NP-Difficiles, nous proposons des heuristiques efficaces pour des réseaux de grande taille. Dans la première partie de cette thèse, nous étudions une solution de routage efficace en énergie dans laquelle nous ajoutons la possibilité d’éliminer des redondances dans les paquets transmis sur le réseau. Nous montrons premièrement que l’ajout de l’élimination des redondances permet d’améliorer l’efficacité énergétique des réseaux en éteignant plus de liens. Ensuite, nous étendons le modèle afin qu’il prenne en compte un certain niveau d’incertitudes dans le volume de trafic et le taux de redondances. La deuxième partie de cette thèse est consacrée aux problèmes qui se posent lors du déploiement de tels protocoles dans les réseaux. Plus particulièrement, nous proposons de minimiser les changements entre deux configurations réseaux consécutives lorsque plusieurs matrices de trafic sont considérées. Le routage des demandes étant alors assuré avec le protocole de routage OSPF (Open Shortest Path First). Ensuite, nous abordons le problème de la limitation du nombre de règles de routage dans les routeurs en utilisant une technologie de type SDN (Software Defined Networks). Enfin, nous présentons en annexe des travaux complémentaires réalisés au cours de cette thèse concernant le routage multicast et le contrôle de congestion TCP. / In this thesis, we study several models of energy-Aware routing. For each model, we present a linear programming formulation to find the exact solution. Moreover, since energy-Aware routing is NP-Hard problem, we also propose efficient heuristic algorithms for large scale networks. In the first part of this thesis, we deal with GreenRE - a new energy-Aware routing model with the support of redundancy elimination. We first present a deterministic model in which we show how to combine energy-Aware routing and redundancy elimination to improve energy efficiency for backbone networks. Then, we extend the model in order to take into account uncertainties in traffic volumes and redundancy rates. The second part of this thesis is devoted to the deployment issues of energy- aware routing in practice. In detail, to avoid service deterioration for end-Users, we limit changes of network configurations in multi-Period traffic matrices in Open Shortest Path First (OSPF) protocol. Next, we address the problem of limited rule space in OpenFlow switches when installing energy-Aware routing configurations. Finally, we present in the appendix other works developed during this thesis: multicast network protocol and TCP congestion control algorithm.

Data processing for Big Data plays a vital role for decision-makers in organizations and government, enhances the user experience, and provides quality results in prediction analysis. However, many modern data processing solutions make a significant investment in hardware and maintenance costs, such as Hadoop and Spark, often neglecting the well established and widely used relational database management systems (RDBMS's). In this dissertation, we study three fundamental graph problems in RDBMS. The first problem we tackle is computing shortest paths (SP) from a source to a target in large network graphs. We explore SQL based solutions and leverage the intelligent scheduling that a RDBMS performs when executing set-at-a-time expansions of graph vertices, which is in contrast to vertex-at-a-time expansions in classical SP algorithms. Our algorithms perform orders of magnitude faster than baselines and outperform counterparts in native graph databases. Second, we studied the PageRank problem which is vital in Google Search and social network analysis to determine how to sort search results and identify important nodes in a graph. PageRank is an iterative algorithm which imposes challenges when implementing it over large graphs. We study computing PageRank using RDBMS for very large graphs using a consumer-grade machine and compare the results to a dedicated graph database. We show that our RDBMS solution is able to process graphs of more than a billion edges in few minutes, whereas native graph databases fail to handle graphs of much smaller sizes. Last, we present a carefully engineered RDBMS solution to the problem of triangle enumeration for very large graphs. We show that RDBMS's are suitable tools for enumerating billions of triangles in billion-scale networks on a consumer grade machine. Also, we compare our RDBMS solution's performance to a native graph database and show that our RDBMS solution outperforms by orders of magnitude. / Graduate

Ce travail de thèse s’est intéressé au transport urbain de passagers dans un contexte d’offre de transport multimodale consistant en la coexistence de plusieurs modes de transport. Dans la pratique, un problème de transport multimodal nécessite la prise en compte de plusieurs objectifs et de contraintes spécifiques liées aux modes ou à la séquence de modes utilisés. De telles contraintes sont appelées contraintes de viabilité.Cette thèse CIFRE s’est déroulée en collaboration avec la société MobiGIS, spécialisée dans le conseil et le développement d’applications autour des Systèmes d’Information Géographiques.Le problème étudié dans cette thèse est celui de la recherche d’itinéraires viables multimodaux point à point bi-objectif pour lequel il s’agit à la fois de minimiser le temps de trajet et le nombre de changements de mode. Compte tenu notamment des objectifs considérés, ce problème est de complexité polynomiale.Sur la base d’une modélisation multi-couches des réseaux de transport multimodaux et d’une modélisation par un automate à états finis des contraintes de viabilité nous avons proposé différents algorithmes de résolution de ce problème basés sur le principe de fixation et extension de labels. Nous avons également proposé une règle de dominance basée sur les états de l’automate de viabilité et permettant d’élaguer le nombre de labels explorés par nos algorithmes. Des adaptations en bidirectionnel ou en utilisant le principe de la recherche A_ ont également été proposées.Les algorithmes proposés ont été évalués sur une partie du réseau de transport de la ville de Toulouse et les expérimentations ont mis en évidence l’intérêt de la règle de dominance basée sur les états ainsi que de l’approche bidirectionnelle développée.Un prototype logiciel implémentant différentes fonctionnalités des algorithmes de plus courts chemins a été développé. Il permet notamment de réaliser des calculs d’itinéraires point à point, des calculs d’accessibilité ou des calculs de distancier / This thesis focuses on urban passenger multimodal transportation. In practice, a multimodal transportation problem requires taking into account several objectives and specific constraints related to modes or sequence of used modes. Such constraints are called viability constraints. This work has been carried out in collaboration with MobiGIS, a company specialized in consulting and development of applications around Geographical Information Systems.The problem studied in this thesis is the bi-objective multimodal viable point-to-point shortest path, aiming at minimizing the total travel time and the total number of mode changes. Given the considered objectives, this problem is polynomial.On the basis of a multi-layered graph model of the multimodal transportation networks, and of a finite state automaton model of the viability constraints, we propose various algorithms for solving this problem, based on the principle of label setting and extension.We also proposed a new dominance rule based on the states of the automaton to reduce the number of labels explored by our algorithms. Bidirectional and A* variants are also proposed.The algorithms are evaluated the transportation network of the city of Toulouse and experiments demonstrate the interest of the proposed dominance rules and bidirectional approach. A prototype software implementing different features of the shortest path algorithms has been developed. It notably enables calculations of point-to-point routes, accessibility and origin-destination matrices

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第21361号 / 工博第4520号 / 新制||工||1704(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 山田 忠史, 教授 藤井 聡, 准教授 SCHMOECKER,Jan-Dirk / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Adoption of electric vehicles has been restrained by the availability of charging stations and consumer fear of being stranded with a depleted battery, far from the nearest charger. In many areas of the world, charging stations are now widely available and the transition from vehicles with internal combustion engines is accelerating, though still in a fairly early stage. For electric vehicle drivers in those areas, anxiety that they will not be able to find a charger (“range anxiety”) is subsiding. However, differences in charging speed and pricing between stations and different outlets at the same station can be large. Total trip duration can vary significantly based on the charging outlet selected. Prior research has developed methods for helping all drivers find the fastest route and for electric vehicle drivers to ensure that they are able to complete their trip. Additional research has explored other complexities of route selection for electric vehicles such as how to select optimal stations for charging based on the total trip duration, including driving and charging time. Pricing for recharging electric vehicles at public chargers is more complex and diverse than for gas filling stations due to the differences in charging rates and the relatively low competition. This research investigates those differences. Using design science research methodology, a method is presented for determining which charging stops result in the lowest possible charging cost for a given route. The method is demonstrated through experiment with random routes within Sweden. The experimental results show that the average cost savings as compared to the duration-optimal route is 15% and 139 SEK per additional hour of trip time. One possible direction for future work is to improve the performance of the algorithm for use in real-time consumer route planning applications.