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This work focuses on path planning for an autonomous UAV to tour and cover multiple regions in the shortest time. The three challenges to be solved are - finding the right optimal order to tour the neighborhoods, determining entry and exit points to neighborhoods, and covering each neighborhood. Two approaches have been explored and compared to achieve this goal - a TSP - Greedy and TSP - Dijkstra's. Both of them use a TSP solution to determine the optimal order of touring. They also use the same back and forth motion to cover each region. However, while the first approach uses a brute force to determine the the next closest node of entry or exit, the second approach utilizes the Dijkstra's algorithm to compute all possible paths to every node in the graph, and therefore choose the shortest pairs of entry and exit for each region, that would generate the shorter path, overall. The main contribution of this work is to implement an existing algorithm to combine the touring and covering problem, and propose a new algorithm to perform the same. Empirical results comparing performances of both approaches are included. Hardware experiments are performed on a spraying hexacopter, using the TSP - Greedy approach. Unique system characteristics are studied to make conclusions about stability of the platform. Future directions are identified to improve both software and hardware performance. / Master of Science

As the interest in electric heavy-duty vehicles has grown, so has the need for route planning tools to coordinate fleets of electric vehicles. This problem is called the Electric Vehicle Routing Problem (EVRP) and it can be solved using a Branch-Price-and-Cut method, where routes for individual vehicles are iteratively generated using information from the coordinated problem. These routes are computed in a pricing problem, which is a Resource Constrained Elementary Shortest Path Problem (RCESPP). Because of its iterative nature, the Branch-Price-and-Cut method is dependent on a fast solver for this RCSPP to get a good computational performance. In this thesis, we have implemented a labeling algorithm for the RCESSP for electric vehicles with state-of-the-art acceleration strategies. We further suggest a new bounding method that exploits the electric aspects of the problem. The algorithm's performance and the effect of the different acceleration strategies are evaluated on benchmark instances for the EVRP, and we report significantly improved computational times when using our bounding method for all types of instances. We find that route relaxation methods (ng-routes) were particularly advantageous in test instances with a combination of clustered and randomly distributed customers. Interestingly, for test instances with only randomly distributed customers, ng-relaxation required longer processing time to achieve elementary optimal routes and for these instances, the bounding methods gave better computational performance.

A*(A-Star)演算法透過啟發函式，以減少路徑搜尋過程中所需要計算的網路數量，SMA*(Simplified Memory Bounded A-Star)為A*之變形，目前最廣泛被應用於GPS導航系統之路徑規劃的演算法。尋找路徑的計算過程中，A*與SMA*演算法利用中間節點與目的地的方向(直線距離)作為啟發函式，以預估中間節點到目的地之路徑長度挑選優先搜尋的路段，而SMA*則因記憶體的限制會排除預估長度較長的路段，以減少搜尋的路段數量與記憶體之使用量。當起點與終點中存在障礙地形時或路段較崎嶇時，以方向導引路徑搜尋之準確度便大幅降低，導致A*與SMA*之搜尋數量增加，SMA*甚至會得到較差的路徑。 主幹導引式最短路徑搜尋演算法(Backbone Orientation)以骨幹路徑導引路徑之搜尋，在障礙地形或道路崎嶇的情況下，可有效避免SMA*之缺點，效能較佳。主幹導引式最短路徑搜尋演算法分為二階段，先由原始路網中提取骨幹路網，並計算出最佳骨幹路徑，再利用骨幹路徑引導路徑的搜尋，在骨幹路徑的一定範圍內搜尋最短路徑。 本研究以台灣地區2007年之平面路網圖進行實驗，以三種不同的實驗方式進行實驗，以驗證主幹導引式最短路徑搜尋演算法之效能，證明在SMA*演算法之啟發函式效能低落時，使用主幹導引式最短路徑搜尋演算法可以有效的改善SMA*在障礙地形之效能不彰的問題。

Efficient energy use is primarily for any sensor networks to function for a longer time period. There have been many efficient schemes with various progress levels proposed by many researchers. Yet, there still more improvements are needed. This thesis is an attempt to make wireless sensor networks with further efficient on energy usage in the network with respect to rate of delivery of the messages. In sensor network architecture radio, sensing and actuators have influence over the power consumption in the entire network. While listening as well as transmitting, energy is consumed by the radio. However, if by reducing listening times or by reducing the number of messages transmitting would reduce the energy consumption. But, in real time scenario with critical information sensing network leads to information loss. To overcome this an adaptive routing technique should be considered. So, that it focuses on saving energy in a much more sophisticated way without reducing the performance of the sensing network transmitting and receiving functionalities. This thesis tackles on parts of the energy efficiency problem in a wireless sensor network and improving delivery rate of messages. To achieve this a routing technique is proposed. In this method, switching between two routing paths are considered and the switching decision taken by the server based on messages delivered comparative previous time intervals. The goal is to get maximum network life time without degrading the number of messages at the server. In this work some conventional routing methods are considered for implementing an approach. This approach is by implementing a shortest path, Gradient based energy routing algorithm and an observer component to control switching between paths. Further, controlled switching done by observer compared to normal initial switch rule. Evaluations are done in a simulation environment and results show improvement in network lifetime in a much more balanced way.

Le contexte écologique et économique actuel incite les autorités et le public à la réduction des émissions de CO2 et les dépendances vis-à-vis des hydrocarbures. Le transport représente 23 % des émissions de polluants dans le monde, et ce chiffre passe à 39 % pour la France. L’adoption de nouvelles solutions de transport est primordiale pour la réduction de ces émissions. L’électromobilité représente une alternative viable aux véhicules thermiques conventionnels. Si les véhicules électriques permettent une mobilité avec zéro émission, certaines de leurs caractéristiques empêchent leur développement. Les principaux freins à l’adoption de ce type de véhicules sont l’autonomie limitée, le faible déploiement des stations de recharge en milieu urbain (et extra urbain) ainsi que les temps de recharge importants. Aussi, afin de promouvoir l’usage de ce type de mobilité, il incombe de développer des outils visant à optimiser la consommation électrique tenant compte des caractéristiques liées à ce type de mobilité. C’est l’objectif de ce travail de thèse qui se focalise sur le développement d’outils permettant d’optimiser l’usage de véhicules électriques. Pour ce faire, trois grands axes sont définis : la modélisation des véhicules électriques, l’affectation des stations de recharge et le choix d’éco-itinéraires. La première partie de cette thèse s’intéresse à l’estimation de la consommation des véhicules électriques ainsi qu’à la présentation de la librairie de modèles dynamiques VEHLIB d’estimation de la consommation de ce type de véhicules. La seconde partie est consacrée à l’affectation optimale des stations de recharge. Une méthodologie de déploiement d’infrastructures de recharge est proposée pour la ville de Lyon avec prise en compte de la demande de mobilité issue des enquêtes ménages déplacements. La troisième partie de la thèse s’intéresse à la thématique du choix d’éco-itinéraire (green routing). Celle-ci aboutit à la proposition d’une méthodologie multi-objectif de recherche de stations de recharge afin de déterminer des itinéraires optimaux avec déviation vers ces stations lorsque l’état de charge de la batterie du véhicule ne permet pas de terminer le trajet. Pour finir, une expérimentation a été réalisée à l’aide d’un véhicule électrique équipé de capteurs de position et de consommation pour d’une part valider les méthodologies proposées et d’autre part analyser les facteurs exogènes qui influent sur la consommation des véhicules électriques. / The current ecological and economic context encourages the authorities and the public to reduce CO2 emissions and oil dependence. The transportation is responsible for 23% of pollutants emissions in the world, and this proportion increases up to 37% in France/ The adoption of new transport solutions is primordial to reduce these emissions. Electro mobility is a viable alternative to conventional vehicles. While electric vehicles offer mobility with zero emissions, some of their characteristicds impede their development. The main obtacle to the adoption of these vehicles is the limited autonomy, a sparse distribution of charging stations in urban areas as well as a significant charging time. Also, to promote the use of this type of mobility, it is primordial to develop tools that optimize the energy consumption and take in to account the characteristics associated with this type of mobility. To achieve this, three areas are difined: modeling of electric vehicles, optimized charging station deployment and eco routing. The first part of this theis focuses on the consumption estimation of the electric vehicles and the presentation of the dynamic model library VEHLIB. The second part is dedicated to optimal allocation of charging stations; A methodology for the deployment of electric vehicle charging infrastructures is proposed for the urban area o fthe city of Lyon, taking into account the mobility demand derived from the household travel surveys.The third part of the thesis deals with the eco-routing (green routing). A multi-objective methodology for eco routing with recharge en-route is proposed. The solutions take into account battery state does not permit to finish the trip.Finally, an experiment was carried out using an electric vehicle equipped with position and consumption sensors in order to validate the proposed methodologies and analyze exogenous factor that impact the electric vehicle consumption.

[pt] A interpretação manual de um horizonte sísmico é um processo muito custoso em termos de tempo de trabalho do intérprete, o que incentiva a pesquisa de métodos automáticos, ou semi automáticos, de rastreamento. Dentre as propostas existentes baseadas em correlação, uma limitação conhecida é o uso de abordagens locais para definir as amostras pertencentes ao horizonte rastreado. Esse tipo de abordagem possui bom desempenho em dados onde não há a presença de falhas sísmicas, porém, nas regiões de baixa coerência, característica das regiões ruidosas ou de falhas, ao tomar uma decisão local o rastreador fica suscetível à propagação de erro. O objetivo deste trabalho é avaliar o uso de algoritmos de menor caminho em grafos para a solução do problema de rastreamento de horizontes sísmicos, afim de propor um método de caráter global que seja robusto a diferentes feições sísmicas. / [en] The manual interpretation of a seismic horizon is a time consuming process, which drives the research for automatic or semi automatic tracking methods. Among the known propositions that use correlation, there is a common limitation: the usage of local approaches to determine which samples belong to the horizon. This kind of approach performs well in data where there are no seismi faults. However, by using only local information, it is prone to error propagation in low coherency areas, which usualy corresponds to fault regions. The goal of this work is to evaluate the performance of shortest path algorithms as a solution for the horizont tracking problem. It intends to propose a global method that is robust to different seismic features.

Este trabalho apresenta um estudo teórico da Técnica de Geração de Colunas (GC) aplicada em alguns Problemas de Roteamento de Veículo (PRV). Essa técnica foi inicialmente utilizada para tratar problemas de otimização de grande porte com estruturas especiais[Dantzig & Wolfe, 1960]. Dentre as diversas classes de problemas de roteamento; revisamos a aplicação dessa técnica a dois casos particulares: O problema de roteamento de helicópteros em plataformas marítimas, cujo objetivo minimizar o custo total do transporte; O problema de roteamento com janela de tempo, onde a função objetivo é descrita pelo tamanho da frota e o custo do percurso. Revisamos e implementamos um algoritmo de caminho mínimo com janela de tempo (CMJT). Esse algoritmo surge como um sub-problema do algoritmo Primai Simplex para resolver o problema de partição de conjunto, utilizado para modelar o problema de roteamento com janela de tempo. / This work presents a study about the Column Generation Technique (CG) applied to some Vehicle Ftouting Problems. The technique was first used to deal with optimization problems having special structures. Among the vaa-ious classes of routing problems, we review the use of the technique in two specific cases: Ftouting helicopters for crew exchanges on off-shore locations, where the objective is to minimize the total transportation cost; Ftouting with time windows, where the objective function is composed by the size of the fleet and the cost of route. We review and implement a shortest path algorithm with time windows. This algorithm aa-ises as a sub-problem in the Primai Simplex algorithm to solve the linear relaxation of the set partitioning problem used to model the routing problem with time windows.

Utilizou-se neste trabalho um sistema de filas contendo três servidores exponenciais, heterogêneos, operando em paralelo. Trocas entre filas são permitidas após o usuário analisar dois aspectos: a diferença entre o tamanho das filas envolvidas na troca e o grau de vizinhança entre elas. O jockeying não é obrigatório, podendo os usuários optar por ele com uma probabilidade de ocorrência de acordo com os aspectos citados. Como resultado deste estudo foi obtida uma equação geral que representa o sistema. O sistema M/(M/1)3 com jockeying probabilístico tem uma ociosidade bem menor que o tradiconal M/Mi/3, alimentado por fila única. Outras características foram analisadas. / We consider a parallel queueing system with three exponential heterogeneous servers where is allowed jockey among queues with no obligation and the customers may choose for it with an occurrence probability after they have been analyzed two aspects: the difference between involved lines lenght in jockeying and the neighborhood degree among them. The effect of this study is a general equation which represents the system. The M/(M/1)3 system with probabilistc jockeying has a smaller idleness than the traditional M/Mi/3 fed from a single queue. We also analysed other characteristics.

Este trabalho apresenta um estudo teórico da Técnica de Geração de Colunas (GC) aplicada em alguns Problemas de Roteamento de Veículo (PRV). Essa técnica foi inicialmente utilizada para tratar problemas de otimização de grande porte com estruturas especiais[Dantzig & Wolfe, 1960]. Dentre as diversas classes de problemas de roteamento; revisamos a aplicação dessa técnica a dois casos particulares: O problema de roteamento de helicópteros em plataformas marítimas, cujo objetivo minimizar o custo total do transporte; O problema de roteamento com janela de tempo, onde a função objetivo é descrita pelo tamanho da frota e o custo do percurso. Revisamos e implementamos um algoritmo de caminho mínimo com janela de tempo (CMJT). Esse algoritmo surge como um sub-problema do algoritmo Primai Simplex para resolver o problema de partição de conjunto, utilizado para modelar o problema de roteamento com janela de tempo. / This work presents a study about the Column Generation Technique (CG) applied to some Vehicle Ftouting Problems. The technique was first used to deal with optimization problems having special structures. Among the vaa-ious classes of routing problems, we review the use of the technique in two specific cases: Ftouting helicopters for crew exchanges on off-shore locations, where the objective is to minimize the total transportation cost; Ftouting with time windows, where the objective function is composed by the size of the fleet and the cost of route. We review and implement a shortest path algorithm with time windows. This algorithm aa-ises as a sub-problem in the Primai Simplex algorithm to solve the linear relaxation of the set partitioning problem used to model the routing problem with time windows.