Flight planning is a large part of the air traffic operations that are presently being conducted. Airlines strive to achieve the cheapest and most cost effective routes for their flights, resulting in aircraft sometimes flying longer routes in order to avoid expensive airspaces with high unit rates. This issue has been an ongoing obstacle for the Swedish air navigation provider, LFV, as some airlines tend to fly over the Baltic Sea, through the Baltic countries, instead of the shorter route through Swedish airspace. These protracted routes result in extra kilometers being flown yearly,consuming extra fuel, as well as imply a revenue loss to LFV and Sweden. The conclusions of this study is that the airspace dodging behavior generate a revenue loss to LFV, totaling approximately €5 032 354 million per year. Should these flights fly the shortest route between their origin and destination, the before mentioned sum would mean an increase in LFV’s reported revenue from air traffic control services by 2%. Airspace dodging also results in roughly 380 408 superfluous kilometers being flown and 1 874 486 liters of additional fuel being consumed every year.

This dissertation progressively addresses research problems related to the trajectory optimization for fuel cell powered UAVs, from propulsion system model development, to optimal trajectory analyses and optimal trajectory applications. A dynamic model of a fuel cell powered UAV propulsion system is derived by combining a fuel cell system dynamic model, an electric motor dynamic model, and a propeller performance model. The influence of the fuel cell system dynamics on the optimal trajectories of a fuel cell powered UAV is investigated in two phases. In the first phase, the optimal trajectories of a fuel cell powered configuration and that of a conventional gas powered configuration are compared for point-to-point trajectory optimization problems with different performance index functions. In the second phase, the influence of the fuel cell system parameters on the optimal fuel consumption cost of the minimum fuel point-to-point optimal trajectories is investigated. This dissertation also presents two applications for the minimum fuel point-to-point optimal trajectories of a fuel cell powered UAV: three-dimensional minimum fuel route planning and path generation, and fuel cell system size optimization with respect to a UAV mission.

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。

Kurs: Examensarbete i logistik för Civilekonomprogrammet, 4FE19E, VT17 Författare: Martin Norén och Kristoffer Nählstedt Handledare: Hana Hulthén Examinator: Helena Forslund Titel: Hemtjänsten i Växjö kommun - En fallstudie om personal- och ruttplanering Bakgrund: Boendeformen särskilt boende har minskat påtagligt de senaste åren och förväntas minska ytterligare i framtiden. Samtidigt ökar andelen äldre som är i behov av vård och omsorg. Ett sätt att lösa detta är att förlägga omsorgsvården på hemtjänsten. För att klara sitt uppdrag använder hemtjänstenheter idag sig av olika planeringsverktyg som är tänkt att säkerställa att en kostnadseffektiv hemtjänst kan bedrivas samtidigt som den inte ska ge avkall på kvalitén av omsorg. Det ökade trycket på hemtjänsten kräver dock mycket resurser och det är idag svårt att klara av att nå upp till de interna målen som ställts på organisationen under denna föränderliga tid. Därför är det viktigare än någonsin med effektiva planeringsprocesser som kan underlätta och stödja hemtjänsten i sina åtaganden. Syfte: Syftet med studien är att effektivisera hemtjänstenheters planeringsprocesser. Avsikten med effektiviseringen är att uppnå en mer kostnadseffektiv hemtjänst som når måluppfyllelsen inom kontinuitet och brukartid. Metod: Studien är en fallstudie som genomförts i Växjö kommuns omsorgsenhet. Med hjälp av semi-strukturerade intervjuer, insamling av kvalitativ och kvantitativ data har studien kunnat inhämta empiriskt material. En processkartläggning genomfördes och författarna identifierade slöserier och presenterade sedan förbättringsförslag med stöd från åtskilliga teorier. Slutsatser: Författarna lyckades lägga fram förbättringsförslag på alla de tre planeringsprocesser som studien lyckades identifiera. Först lades förbättringsförslag av både kvantitativ och kvalitativ karaktär fram med avsikten att säkerställa kompetensförsörjningen i organisationen. I ruttplaneringsprocessen delade författarna upp hemtjänstenheten Vikaholm i två olika grupper baserat på dess geografiska placeringar och lyckades därigenom förbättra både kontinuiteten och brukartiden samtidigt som kostnaden sjönk för organisationen som helhet. Efter observationer och intervjuer på de olika arbetsgrupperna framkom slutligen fler förbättringsförslag på hur hemtjänstenheter skulle kunna arbeta för att effektivisera sin schemaläggningsprocess ytterligare. Nyckelord: Hemtjänst, äldreomsorg, kontinuitet, brukartid, planering, planeringsprocesser, processkartläggning, ruttplanering, prognostisering. / Course: Examensarbete i logistik för Civilekonomprogrammet, 4FE19E, VT17 Authors: Martin Norén and Kristoffer Nählstedt Tutor: Hana Hulthén Examiner: Helena Forslund Title: Home care for the elders in Växjö municipality - A case study about personnel and route planning Background: In Sweden the amount of people living in an assisted living have reduced significantly during the recent years and is predicted to be reduced even more. At the mean time the amount of elders in need of care is increasing. One way of solving this is by the use of home care. To handle its duty home care units use different kinds of planning tools to ensure quality of the care and that the home care is being cost efficient. The increased demand on the home care service requires a lot of resources and it is today very hard to achieve the internal goals which have been set up by the organisation. Therefore it is now more important than ever with efficient planning processes that can ease and support the home care service in its obligations. Purpose: The purpose of the study is to streamline the planning process in elder care units. The streamlined planning process intends to achieve a more cost efficient elder care, that achieves the objectives concerning continuity and time spent with the elders. Method: The study is a case study, which have been carried out in the municipality of Växjö. With the use of semi-structured interviews, gathering of qualitative and quantitative data the study have been able to obtain empirical material. In order to identify waste the authors used process mapping and then later on proposed improvements with support from a number of theories. Conclusions: The authors managed to propose improvements on all of three identified planning processes. Firstly, the study presented the proposed improvements on the process of ensuring competent personnel with the use of both qualitative and quantitative data. In the route planning process the authors split the home care unit of Vikaholm into two units, based on the locations of the elders. Thereby the authors managed to improve all of the three main goals of the home care unit; continuity, economy and the amount of time the care takers spend with the elders. Observations and interviews on the different units lead to the conclusion of potential improvements on how home care units could work to be more efficient in their scheduling processes.  Keywords: Home care, elder care, time spent with the elder, planning, process planning, process mapping, route planning, forecasting.

A segurança nos voos de Veículos Aéreos Não Tripulados (VANTs) é uma importante questão e vem ganhando destaque devido a uma série de acidentes com tais aeronaves. O aumento do número de aeronaves no espaço aéreo e a autonomia cada vez maior para realizar missões estão entre outros elementos que merecem destaques. No entanto, pouca atenção tem sido dada a autonomia da aeronave em casos emergenciais [Contexto]. Nesse contexto, o desenvolvimento de algoritmos que efetuem o planejamento de rotas na ocorrência de situações críticas é fundamental para obter maior segurança aérea. Eventuais situações de insegurança podem estar relacionadas a uma falha nos equipamentos do veículo aéreo que impede a continuação da missão em curso pela aeronave [Lacuna]. A presente pesquisa avança o estado da arte considerando um conceito chamado In-Flight Awareness (IFA), que estabelece consciência situacional em VANTs, visando maior segurança de voo. Os estudos também avançam na proposição de modelos matemáticos que representem o estado da aeronave avariada, viabilizando o pouso emergencial e minimizando possíveis danos [Propósito]. Este trabalho utiliza técnicas de computação evolutiva como Algoritmos Genéticos (AG) e Algoritmos Genéticos Multi-Populacional (AGMP), além de uma Heurística Gulosa (HG) e um modelo de Programação Linear Inteira Mista (PLIM) no tratamento de falhas críticas juntamente com o conceito de IFA [Metodologia]. As soluções obtidas foram avaliadas através de experimentos offline usando os modelos matemáticos desenvolvidos, além de validadas em um simulador de voo e em um voo real. De forma geral, o AG e AGMP obtiveram resultados equivalentes, salvando o VANT em aproximadamente 89% dos mapas. A HG conseguiu trazer a aeronave até uma região bonificadora em 77% dos mapas dentro de um tempo computacional abaixo de 1 segundo. No modelo PLIM, o tempo gasto foi de cerca de quatro minutos já que garantia a otimalidade da solução encontrada. Devido ao seu elevado tempo computacional, uma estratégia evolvendo rotas pré-calculadas foi definida a partir do PLIM, mostrando-se bastante promissora. Nos experimentos envolvendo simulador de voo foram testadas diferentes condições de vento e se verificou que mesmo sobre tais condições os métodos desenvolvidos conseguiram efetuar o pouso com segurança [Resultado]. O trabalho apresentado colabora com a segurança de Veículos Aéreos Não Tripulados e com a proposta de modelos matemáticos que representem a aeronave em caso de situações críticas. Os métodos, de forma geral, mostraram-se promissores na resolução do problema de pouso emergencial já que trouxeram a aeronave com segurança até regiões interessantes ao pouso em um baixo tempo computacional. Isso foi atestado pelos resultados obtidos a partir das simulações offline, em simulador de voo e em voo real [Conclusão]. As principais contribuições do trabalho são: modelagem de regiões adequadas ao pouso, modelagem de falhas, arquitetura do sistema planejador de rotas e modelo linear para para pouso emergencial [Contribuição]. / The security involved in flights of Unmanned Aerial Vehicles (UAVs) is an important issue and is achieving prominence due to a number of accidents involving such aircraft. Other elements that deserve highlights are the increase in the number of aircraft in the airspace and autonomy to perform missions, however, little attention has been given to the autonomy of the aircraft in emergency cases [Context]. In this context, the development of algorithms that contribute significantly to the path planning in the event of critical situations is essential for more air traffic. Possible situations of insecurity may be related to a failure in the equipment of vehicle that prevents the continuation of the current mission by aircraft [Gap]. The research advances the state of the art considering a concept called In-Flight Awareness (IFA), which provides situational awareness in UAVs aiming at greater flight safety. Advances also in the developing of mathematical models that represent the state of the damaged aircraft, with the purpose to execute the emergency landing by minimizing damages [Purpose]. Thus, this work applies evolutionary computation techniques such as Genetic Algorithms (GA) and Multi-Population Genetic Algorithms (MPGA), as well as a Greedy Heuristic (GH) and a Mixed Integer Linear Programming (MILP) model to deal with critical situations along with the concept of IFA [Methodology]. The solutions obtained were evaluated through offline experiments using the developed mathematical models, which were validated in a flight simulator and a real-world flight. In General, the GA and MPGA reached similar results by saving the UAV in approximately 89% of the maps, while the GH was able to bring the aircraft to a bonus region for 77% of maps within a feasible computational time lower than 1 second. In the MILP model, the time spent was about four minutes since it guarantees optimality of the solution found. Due to such high computational time, a strategy involving nearby routes pre-calculated was defined from the MILP which was very promising. In experiments involving flight simulator, different wind conditions were tested and it was found that even under such conditions the methods developed have managed to execute the landing safely [Result]. The work presented collaborates with the safety of Unmanned Aerial Vehicles and with the proposal of mathematical models that represent the aircraft under critical situations. The methods, in general, were promising since they brought the aircraft to execute a safe landing within a low computational time as shown by offline simulations, flight simulator and real flight [Conclusion]. The main contributions are: fault modeling, system architecture planner routes and linear model for emergency landing. [Contribution].

<p>The transportation cost of logs from forest to customers is a large part of the overall cost for the Swedish forestry industry. Finding good routes from harvesting points to saw and pulp mills is a complex task, where the total number of feasible routes is extremely high. In this thesis we present two methods for log truck scheduling. </p><p>The first is to, from a given set of routes, find the most valuable subset that fulfils the customers demand. We use a model that is similar to the set partitioning problem and a method that is referred to as a composite pricing coupled with Branch and Bound. The composite pricing based method prices the routes (columns) and chooses the most valuable ones that are then added to the LP relaxation. Once an LP optimum is found, the Branch and Bound method is used to find an integer optimum solution. We have tested this on a case of realistic size. </p><p>The second method is a tabu search heuristic. Here, the purpose is to create efficient and qualitative routes from a given number of trips (referred to as predefined trips). From a start solution tabu search systematically generates new solutions. This method was tested on a small problem and on a five times larger problem to study how the size of the problem affected the result. It was also tested and compared on two cases in which the backhauling possibilities (i.e. instead of traveling empty the truck picks up another load on the return trip) had and had not been studied. The composite pricing based method and the tabu search method proved to be very useful for this kind of scheduling.</p>

The transportation cost of logs from forest to customers is a large part of the overall cost for the Swedish forestry industry. Finding good routes from harvesting points to saw and pulp mills is a complex task, where the total number of feasible routes is extremely high. In this thesis we present two methods for log truck scheduling. The first is to, from a given set of routes, find the most valuable subset that fulfils the customers demand. We use a model that is similar to the set partitioning problem and a method that is referred to as a composite pricing coupled with Branch and Bound. The composite pricing based method prices the routes (columns) and chooses the most valuable ones that are then added to the LP relaxation. Once an LP optimum is found, the Branch and Bound method is used to find an integer optimum solution. We have tested this on a case of realistic size. The second method is a tabu search heuristic. Here, the purpose is to create efficient and qualitative routes from a given number of trips (referred to as predefined trips). From a start solution tabu search systematically generates new solutions. This method was tested on a small problem and on a five times larger problem to study how the size of the problem affected the result. It was also tested and compared on two cases in which the backhauling possibilities (i.e. instead of traveling empty the truck picks up another load on the return trip) had and had not been studied. The composite pricing based method and the tabu search method proved to be very useful for this kind of scheduling.

Der Aufenthaltsort eines mobilen Benutzers stellt eine wichtige Information für Anwendungen aus den Bereichen Mobile Computing, Wearable Computing oder Ubiquitous Computing dar. Ist ein mobiles Endgerät in der Lage, die aktuelle Position des Benutzers zu bestimmen, kann diese Information von der Anwendung berücksichtigt werden -- man spricht dabei allgemein von ortsbezogenen Anwendungen. Eng verknüpft mit dem Begriff der ortsbezogenen Anwendung ist der Begriff des ortsbezogenen Dienstes. Hierbei handelt es sich beispielsweise um einen Dienst, der Informationen über den aktuellen Standort übermittelt. Mittlerweile werden solche Dienste kommerziell eingesetzt und erlauben etwa, dass ein Reisender ein Hotel, eine Tankstelle oder eine Apotheke in der näheren Umgebung findet. Man erwartet, nicht zuletzt durch die Einführung von LTE, ein großes Potenzial ortsbezogener Anwendungen für die Zukunft. Das jährlich stattfindende Fachgespräch "Ortsbezogene Anwendungen und Dienste" der GI/ITG-Fachgruppe Kommunikation und Verteilte Systeme hat sich zum Ziel gesetzt, aktuelle Entwicklungen dieses Fachgebiets in einem breiten Teilnehmerkreis aus Industrie und Wissenschaft zu diskutieren. Der vorliegende Konferenzband fasst die Ergebnisse des neunten Fachgesprächs zusammen. / The location of a mobile user poses an important information for applications in the scope of Mobile Computung, Wearable Computing and Ubiquitous Computing. If a mobile device is able to determine the current location of its user, this information may be taken into account by an application. Such applications are called a location-based applications. Closely related to location-based applications are location-based services, which for example provides the user informations about his current location. Meanwhile such services are deployed commercially and enable travelers for example to find a hotel, a petrol station or a pharmacy in his vicinity. It is expected, not least because of the introduction of LTE, a great potential of locations-based applications in the future. The annual technical meeting "Location-based Applications and Services" of the GI/ITG specialized group "Communication and Dsitributed Systems" targets to discuss current evolutions in a broad group of participants assembling of industrial representatives and scientists. The present proceedings summarizes the result of the 9th annual meeting.

Taxis equipped with GPS sensors are an important sensory device for examining people's movements and activities. They are not constrained to a pre-defined schedule/route. Big taxi GPS data recording the spatio-temporal traces left by taxis provides rich and detailed glimpse into the motivations, behaviours, and resulting dynamics of a city's mobile population through the road network. In this dissertation, we aim to uncover the "hidden facets" regarding social and community dynamics encoded in the taxi GPS data to better understand how urban population behaves and the resulting dynamics in the city. As some "hidden facets" are with regard to similar aspect of social and community dynamics, we further formally define three categories for study (i.e. social dynamics, traffic dynamics, and operational dynamics), and explore them to fill the wide gaps between the raw taxi GPS data and innovative applications and smart urban services. Specifically, 1. To enable applications of real-time taxi fraud alerts, we propose iBOAT algorithm which is capable of detecting anomalous trajectories "on-the-fly" and identifying which parts of the trajectory are responsible for its anomalousness, by comparing them against historically trajectories having the same origin and destination. 2. To introduce cost-effective and environment-friendly transport services to citizens, we propose B-Planner which is a two-phase approach, to plan bi-directional night bus routes leveraging big taxi GPS data. 3. To offer a personalized, interactive, and traffic-aware trip route planning system to users, we propose TripPlanner system which contains both offline and online procedures, leveraging a combination of Location-based Social Network (i.e. LBSN) and taxi GPS data sets. Finally, some promising research directions for future work are pointed out, which mainly attempt to fuse taxi GPS data with other data sets to provide smarter and personalized urban services for citizens

Robot motion planning is one of the central problems in robotics, and has received considerable amount of attention not only from roboticists but also from the control and artificial intelligence (AI) communities. Despite the different types of applications and physical properties of robotic systems, many high-level tasks of autonomous systems can be decomposed into subtasks which require point-to-point navigation while avoiding infeasible regions due to the obstacles in the workspace. This dissertation aims at developing a new class of sampling-based motion planning algorithms that are fast, efficient and asymptotically optimal by employing ideas from Machine Learning (ML) and Dynamic Programming (DP). First, we interpret the robot motion planning problem as a form of a machine learning problem since the underlying search space is not known a priori, and utilize random geometric graphs to compute consistent discretizations of the underlying continuous search space. Then, we integrate existing DP algorithms and ML algorithms to the framework of sampling-based algorithms for better exploitation and exploration, respectively. We introduce a novel sampling-based algorithm, called RRT#, that improves upon the well-known RRT* algorithm by leveraging value and policy iteration methods as new information is collected. The proposed algorithms yield provable guarantees on correctness, completeness and asymptotic optimality. We also develop an adaptive sampling strategy by considering exploration as a classification (or regression) problem, and use online machine learning algorithms to learn the relevant region of a query, i.e., the region that contains the optimal solution, without significant computational overhead. We then extend the application of sampling-based algorithms to a class of stochastic optimal control problems and problems with differential constraints. Specifically, we introduce the Path Integral - RRT algorithm, for solving optimal control of stochastic systems and the CL-RRT# algorithm that uses closed-loop prediction for trajectory generation for differential systems. One of the key benefits of CL-RRT# is that for many systems, given a low-level tracking controller, it is easier to handle differential constraints, so complex steering procedures are not needed, unlike most existing kinodynamic sampling-based algorithms. Implementation results of sampling-based planners for route planning of a full-scale autonomous helicopter under the Autonomous Aerial Cargo/Utility System Program (AACUS) program are provided.