Dissertations / Theses on the topic 'Optimization paths'
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Lorek, David Randolph. "Approximating shortest paths in large networks /." Electronic version (PDF), 2005. http://dl.uncw.edu/etd/2005/lorekd/davidlorek.pdf.
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Stout, Kevin Dale. "Design optimization of thermal paths in spacecraft systems." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/82492.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2013.This electronic version was submitted and approved by the author's academic department as part of an electronic thesis pilot project. The certified thesis is available in the Institute Archives and Special Collections.
"June 2013." Cataloged from department-submitted PDF version of thesis
Includes bibliographical references (p. 100-101).
This thesis introduces a thermal design approach to increase thermal control system performance and decrease reliance on system resources, e.g., mass. Thermal design optimization has lagged other subsystems because the thermal subsystem is not thought to significantly drive performance or resource consumption. However, there are factors present in many spacecraft systems that invalidate this assumption. Traditional thermal design methods include point designs where experts make key component selection and sizing decisions. Thermal design optimization literature primarily focuses on optimization of the components in isolation from other parts of the thermal control system, restricting the design space considered. The collective thermal design optimization process formulates the thermal path design process as an optimization problem where the design variables are updated for each candidate design. Parametric model(s) within the optimizer predict the performance and properties of candidate designs. The thermal path parameterization captures the component interactions with each other, the system, and the space environment, and is critical to preserving the full design space. The optimal design is a thermal path with higher performance and decreased resource consumption compared to traditional thermal design methods. The REgolith X-ray Imaging Spectrometer (REXIS) payload instrument serves as a case study to demonstrate the collective thermal design optimization process. First, a preliminary thermal control system model of a point design is used to determine the critical thermal path within REXIS: the thermal strap and radiator assembly. The collective thermal design optimization process is implemented on the thermal strap and radiator thermal path. Mass minimization is the objective and the REXIS detector operational temperature is a constraint to the optimization. This approach offers a 37% reduction in mass of the thermal strap and radiator assembly over a component-level optimization method.
by Kevin Dale Stout.
S.M.
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Wang, I.-Lin. "Shortest paths and multicommodity network flows." Diss., Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/23304.
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Chou, Chang-Chien. "Minimum traversal path of n circles path planning of circles, computing and constructing paths of circles, geometrical optimization." Saarbrücken VDM Verlag Dr. Müller, 2007. http://d-nb.info/991344146/04.
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Garcia, Renan. "Resource constrained shortest paths and extensions." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/28268.
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Thesis (M. S.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2009.Committee Co-Chair: George L. Nemhauser; Committee Co-Chair: Shabbir Ahmed; Committee Member: Martin W. P. Savelsbergh; Committee Member: R. Gary Parker; Committee Member: Zonghao Gu.
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Muhandiramge, Ranga. "Maritime manoeuvring optimization : path planning in minefield threat environments." University of Western Australia. School of Mathematics and Statistics, 2008. http://theses.library.uwa.edu.au/adt-WU2009.0015.
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The aim of the research project that is the subject of this thesis is to apply mathematical techniques, especially those in the area of operations research, to the problem of maritime minefield transit. We develop several minefield models applicable to different aspects of the minefield problem. These include optimal mine clearance, shortest time traversal and time constrained traversal. We hope the suite of models and tools developed will help make mine field clearance and traversal both safer and more efficient and that exposition of the models will bring a clearer understanding of the mine problem from a mathematical perspective. In developing the solutions to mine field models, extensive use is made of network path planning algorithms, particularly the Weight Constrained Shortest Path Problem (WCSPP) for which the current state-of-the-art algorithm is extended. This is done by closer integration of Lagrangean relaxation and preprocessing to reduce the size of the network. This is then integrated with gap-closing algorithms based on enumeration to provide optimal or near optimal solutions to the path planning problem. We provide extensive computational evidence on the performance of our algorithm and compare it to other algorithms found in the literature. This tool then became fundamental in solving various separate minefield models. Our models can be broadly separated into obstacle models in which mine affected regions are treated as obstacles to be avoided and continuous threat in which each point of space has an associated risk. In the later case, we wish to find a path that minimizes the integral of the risk along the path while constraining the length of the path. We call this the Continuous Euclidean Length Constrained Minimum Cost Path Problem (C-LCMCPP), for which we present a novel network approach to solving this continuous problem. This approach results in being able to calculate a global lower bound on a non-convex optimization problem.
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Nilsson, Mikael. "On the Complexity of Finding Spanner Paths." Linköpings universitet, Artificiell intelligens och integrerad datorsystem, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93332.
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We study the complexity of finding so called spanner paths between arbitrary nodes in Euclidean graphs. We study both general Euclidean graphs and a special type of graphs called Integer Graphs. The problem is proven NP-complete for general Euclidean graphs with non-constant stretches (e.g. (2n)^(3/2) where n denotes the number of nodes in the graph). An algorithm solving the problem in O(2^(0.822n)) is presented. Integer graphs are simpler and for these special cases a better algorithm is presented. By using a partial order of so called Images the algorithm solves the spanner path problem using O(2^(c(\log n)^2)) time, where c is a constant depending only on the stretch.
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Turner, Lara Ruth [Verfasser]. "Universal Combinatorial Optimization: Matroid Bases and Shortest Paths / Lara Ruth Turner." München : Verlag Dr. Hut, 2013. http://d-nb.info/1033041297/34.
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Heni, Hamza. "Optimization of time-dependent routing problems considering dynamic paths and fuel consumption." Doctoral thesis, Université Laval, 2018. http://hdl.handle.net/20.500.11794/32805.
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Ces dernières années, le transport de marchandises est devenu un défi logistique à multiples facettes. L’immense volume de fret a considérablement augmenté le flux de marchandises dans tous les modes de transport. Malgré le rôle vital du transport de marchandises dans le développement économique, il a également des répercussions négatives sur l’environnement et la santé humaine. Dans les zones locales et régionales, une partie importante des livraisons de marchandises est transportée par camions, qui émettent une grande quantité de polluants. Le Transport routier de marchandises est un contributeur majeur aux émissions de gaz à effet de serre (GES) et à la consommation de carburant. Au Canada, les principaux réseaux routiers continuent de faire face à des problèmes de congestion. Pour réduire significativement l’impact des émissions de GES reliées au transport de marchandises sur l’environnement, de nouvelles stratégies de planification directement liées aux opérations de routage sont nécessaires aux niveaux opérationnel, environnemental et temporel. Dans les grandes zones urbaines, les camions doivent voyager à la vitesse imposée par la circulation. Les embouteillages ont des conséquences défavorables sur la vitesse, le temps de déplacement et les émissions de GES, notamment à certaines périodes de la journée. Cette variabilité de la vitesse dans le temps a un impact significatif sur le routage et la planification du transport. Dans une perspective plus large, notre recherche aborde les Problèmes de distribution temporels (Time-Dependent Distribution Problems – TDDP) en considérant des chemins dynamiques dans le temps et les émissions de GES. Considérant que la vitesse d’un véhicule varie en fonction de la congestion dans le temps, l’objectif est de minimiser la fonction de coût de transport total intégrant les coûts des conducteurs et des émissions de GES tout en respectant les contraintes de capacité et les restrictions de temps de service. En outre, les informations géographiques et de trafic peuvent être utilisées pour construire des multigraphes modélisant la flexibilité des chemins sur les grands réseaux routiers, en tant qu’extension du réseau classique des clients. Le réseau physique sous-jacent entre chaque paire de clients pour chaque expédition est explicitement considéré pour trouver des chemins de connexion. Les décisions de sélection de chemins complètent celles de routage, affectant le coût global, les émissions de GES, et le temps de parcours entre les nœuds. Alors que l’espace de recherche augmente, la résolution des Problèmes de distribution temporels prenant en compte les chemins dynamiques et les vitesses variables dans le temps offre une nouvelle possibilité d’améliorer l’efficacité des plans de transport... Mots clés : Routage dépendant du temps; chemins les plus rapides dépendant du temps; congestion; réseau routier; heuristique; émissions de gaz à effet de serre; modèles d’émission; apprentissage superviséIn recent years, freight transportation has evolved into a multi-faceted logistics challenge. The immense volume of freight has considerably increased the flow of commodities in all transport modes. Despite the vital role of freight transportation in the economic development, it also negatively impacts both the environment and human health. At the local and regional areas, a significant portion of goods delivery is transported by trucks, which emit a large amount of pollutants. Road freight transportation is a major contributor to greenhouse gas (GHG) emissions and to fuel consumption. To reduce the significant impact of freight transportation emissions on environment, new alternative planning and coordination strategies directly related to routing and scheduling operations are required at the operational, environmental and temporal dimensions. In large urban areas, trucks must travel at the speed imposed by traffic, and congestion events have major adverse consequences on speed level, travel time and GHG emissions particularly at certain periods of day. This variability in speed over time has a significant impact on routing and scheduling. From a broader perspective, our research addresses Time-Dependent Distribution Problems (TDDPs) considering dynamic paths and GHG emissions. Considering that vehicle speeds vary according to time-dependent congestion, the goal is to minimize the total travel cost function incorporating driver and GHG emissions costs while respecting capacity constraints and service time restrictions. Further, geographical and traffic information can be used to construct a multigraph modeling path flexibility on large road networks, as an extension to the classical customers network. The underlying physical sub-network between each pair of customers for each shipment is explicitly considered to find connecting road paths. Path selection decisions complement routing ones, impacting the overall cost, GHG emissions, the travel time between nodes, and thus the set of a feasible time-dependent least cost paths. While the search space increases, solving TDDPs considering dynamic paths and time-varying speeds may provide a new scope for enhancing the effectiveness of route plans. One way to reduce emissions is to consider congestion and being able to route traffic around it. Accounting for and avoiding congested paths is possible as the required traffic data is available and, at the same time, has a great potential for both energy and cost savings. Hence, we perform a large empirical analysis of historical traffic and shipping data. Therefore, we introduce the Time-dependent Quickest Path Problem with Emission Minimization, in which the objective function comprises GHG emissions, driver and congestion costs. Travel costs are impacted by traffic due to changing congestion levels depending on the time of the day, vehicle types and carried load. We also develop time-dependent lower and upper bounds, which are both accurate and fast to compute. Computational experiments are performed on real-life instances that incorporate the variation of traffic throughout the day. We then study the quality of obtained paths considering time-varying speeds over the one based only on fixed speeds... Keywords : Time-dependent routing; time-dependent quickest paths; traffic congestion; road network; heuristic; greenhouse gas emissions; emission models; supervised learning.
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Murekatete, Rachel Mundeli. "An Analysis of Consequences of Land Evaluation and Path Optimization." Licentiate thesis, KTH, Geoinformatik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-235687.
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Planners who are involved in locational decision making often use raster-based geographic information systems (GIS) to quantify the value of land in terms of suitability or cost for a certain use. From a computational point of view, this process can be seen as a transformation of one or more sets of values associated with a grid of cells into another set of such values through a function reflecting one or more criteria. While it is generally anticipated that different transformations lead to different ‘best’ locations, little has been known on how such differences arise (or do not arise). Examples of such spatial decision problems can be easily found in the literature and many of them concern the selection of a set of cells (to which the land use under consideration is allocated) from a raster surface of suitability or cost depending on context. To facilitate GIS’s algorithmic approach, it is often assumed that the quality of the set of cells can be evaluated as a whole by the sum of their cell values. The validity of this assumption must be questioned, however, if those values are measured on a scale that does not permit arithmetic operations. Ordinal scale of measurement in Stevens’s typology is one such example. A question naturally arises: is there a more mathematically sound and consistent approach to evaluating the quality of a path when the quality of each cell of the given grid is measured on an ordinal scale? The thesis attempts to answer the questions highlighted above in the context of path planning through a series of computational experiments using a number of random landscape grids with a variety of spatial and non-spatial structures. In the first set of experiments, we generated least-cost paths on a number of cost grids transformed from the landscape grids using a variety of transformation parameters and analyzed the locations and (weighted) lengths of those paths. Results show that the same pair of terminal cells may well be connected by different least-cost paths on different cost grids though derived from the same landscape grid and that the variation among those paths is affected by how given values are distributed in the landscape grid as well as by how derived values are distributed in the cost grids. Most significantly, the variation tends to be smaller when the landscape grid contains more distinct patches of cells potentially attracting or distracting cost-saving passage or when the cost grid contains a smaller number of low-cost cells. The second set of experiments aims to compare two optimization models, minisum and minimax (or maximin) path models, which aggregate the values of the cells associated with a path using the sum function and the maximum (or minimum) function, respectively. Results suggest that the minisum path model is effective if the path search can be translated into the conventional least-cost path problem, which aims to find a path with the minimum cost-weighted length between two terminuses on a ratio-scaled raster cost surface, but the minimax (or maximin) path model is mathematically sounder if the cost values are measured on an ordinal scale and practically useful if the problem is concerned not with the minimization of cost but with the maximization of some desirable condition such as suitability.Planerare som arbetar bland annat med att fatta beslut som hänsyftar till vissa lokaler använder ofta rasterbaserade geografiska informationssystem (GIS) för att sätta ett värde på marken med avseende på lämplighet eller kostnad för en viss användning. Ur en beräkningssynpunkt kan denna process ses som en transformation av en eller flera uppsättningar värden associerade med ett rutnät av celler till en annan uppsättning sådana värden genom en funktion som återspeglar ett eller flera kriterier. Medan det generellt förväntas att olika omvandlingar leder till olika "bästa" platser, har lite varit känt om hur sådana skillnader uppstår (eller inte uppstår). Exempel på sådana rumsliga beslutsproblem kan lätt hittas i litteraturen och många av dem handlar om valet av en uppsättning celler (som markanvändningen övervägs tilldelas) från en rasteryta av lämplighet eller kostnad beroende på kontext. För att underlätta GISs algoritmiska tillvägagångssätt antas det ofta att kvaliteten på uppsättningen av celler kan utvärderas som helhet genom summan av deras cellvärden. Giltigheten av detta antagande måste emellertid ifrågasättas om dessa värden mäts på en skala som inte tillåter aritmetiska transformationer. Användning av ordinal skala enligt Stevens typologi är ett exempel av detta. En fråga uppstår naturligt: Finns det ett mer matematiskt sunt och konsekvent tillvägagångssätt för att utvärdera kvaliteten på en rutt när kvaliteten på varje cell i det givna rutnätet mäts med ordinalskala? Avhandlingen försöker svara på ovanstående frågor i samband med ruttplanering genom en serie beräkningsexperiment med hjälp av ett antal slumpmässigt genererade landskapsnät med en rad olika rumsliga och icke-rumsliga strukturer. I den första uppsättningen experiment genererade vi minsta-kostnad rutter på ett antal kostnadsnät som transformerats från landskapsnätverket med hjälp av en mängd olika transformationsparametrar, och analyserade lägen och de (viktade) längderna för dessa rutter. Resultaten visar att samma par ändpunkter mycket väl kan vara sammanbundna med olika minsta-kostnad banor på olika kostnadsraster härledda från samma landskapsraster, och att variationen mellan dessa banor påverkas av hur givna värden fördelas i landskapsrastret såväl som av hur härledda värden fördelas i kostnadsrastret. Mest signifikant är att variationen tenderar att vara mindre när landskapsrastret innehåller mer distinkta grupper av celler som potentiellt lockar eller distraherar kostnadsbesparande passage, eller när kostnadsrastret innehåller ett mindre antal låg-kostnad celler. Den andra uppsättningen experiment syftar till att jämföra två optimeringsmodeller, minisum och minimax (eller maximin) sökmodeller, vilka sammanställer värdena för cellerna som är associerade med en sökväg med summanfunktionen respektive maximum (eller minimum) funktionen. Resultaten tyder på att minisumbanemodellen är effektiv om sökningen av sökvägen kan översättas till det konventionella minsta kostnadsproblemet, vilket syftar till att hitta en väg med den minsta kostnadsvägda längden mellan två terminaler på en ratio-skalad rasterkostyta, men minimax (eller maximin) banmodellen är matematiskt sundare om kostnadsvärdena mäts i ordinär skala och praktiskt användbar om problemet inte bara avser minimering av kostnad men samtidigt maximering av någon önskvärd egenskap såsom lämplighet.
QC 20181002
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Nam, Kijin. "Optimization of paths and locations of water quality monitoring systems in surface water environments." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/24745.
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Thesis (Ph.D.)--Civil and Environmental Engineering, Georgia Institute of Technology, 2009.Committee Chair: Aral, Mustafa; Committee Member: Guan, Jiabao; Committee Member: Kim, Seong-Hee; Committee Member: Roberts, Philip; Committee Member: Uzer, Turgay.
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Brown, Geoffrey L. "Nonlinear Locomotion: Mechanics, energetics, and optimality of walking in circles and other curved paths." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1339169797.
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Vladu, Adrian Valentin. "Shortest paths, Markov chains, matrix scaling and beyond : improved algorithms through the lens of continuous optimization." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112828.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mathematics, 2017.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 289-302).
In this thesis, we build connections between classic methods from convex optimization and the modern toolkit from the fast Laplacian solver literature, in order to make progress on a number of fundamental algorithmic problems: *-- We develop a faster algorithm for the unit capacity minimum cost flow problem, which encompasses the shortest path with negative weights and minimum cost bipartite perfect matching problems. In the case of sparse graphs, this provides the first running time improvement for these problems in over 25 years. *-- We initiate the study of solving linear systems involving directed Laplacian matrices, and devise an almost-linear time algorithm for this task. This primitive enables us to also obtain almost-linear time algorithms for computing an entire host of quantities associated with Markov chains, such as stationary distributions, personalized PageRank vectors, hitting times, or escape probabilities. This significantly improves over the previous state-of-the-art, which was based on simulating random walks, or applying fast matrix multiplication. *-- We develop faster algorithms for scaling and balancing nonnegative matrices, two fundamental problems in scientific computing, significantly improving over the previously known best running times. In particular, if the optimal scalings/balancings have polynomially bounded condition numbers, our algorithms run in nearly-linear time. Beyond that, we leverage and extend tools from convex geometry in order to design an algorithm for online pricing with nearly-optimal regret. We also use convex optimization to shed a new light on the approximate Caratheodory problem, for which we give a deterministic nearly-linear time algorithm, as well as matching lower bounds.
by Adrian Valentin Vladu.
Ph. D.
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Yelamarthi, Kumar. "Process Variation-Aware Timing Optimization with Load Balance of Multiple Paths in Dynamic and Mixed-Static-Dynamic CMOS Logic." Wright State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=wright1213880942.
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Souza, Marcelo de. "Um método biobjetivo de alocação de tráfego para veículos convencionais e elétricos." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2015. http://hdl.handle.net/10183/130509.
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A busca de soluções para a mobilidade urbana que minimizem a agressão do setor de tráfego e transportes ao meio ambiente está cada vez maior. Os veículos elétricos se posicionam como uma alternativa interessante, pois reduzem a emissão de gases poluentes na atmosfera, a poluição sonora e o consumo de petróleo. No entanto, sua limitada autonomia e a escassez de postos de recarga intimidam sua adoção. Por conta disso, políticas governamentais de incentivo têm sido desenvolvidas para a oferta de benefícios a quem optar por um veículo elétrico. Estima-se que dentro de poucas décadas toda a frota urbana será substituída por veículos dessa natureza. Por isso, é importante entender as mudanças no tempo de viagem e no consumo de energia oriundos da inclusão de veículos elétricos em cenários de tráfego. Trabalhos anteriores estudaram as diferenças entre os mecanismos internos de veículos convencionais e elétricos na determinação destas mudanças. Porém, dadas as características destes últimos, motoristas de veículos elétricos se preocupam com a economia de energia e podem optar por rotas diferentes. Logo, uma análise completa destes impactos deve considerar uma nova distribuição de tráfego. Este trabalho propõe um método biobjetivo de alocação de tráfego que considera o tempo de viagem e o consumo de energia para determinar a distribuição de veículos elétricos em cenários de tráfego urbano. Duas estratégias de distribuição de fluxo são propostas como mecanismos de escolha de rotas. Como parte da alocação de tráfego, é proposto um algoritmo biobjetivo de caminhos mínimos para veículos elétricos. A abordagem apresentada foi aplicada a três cenários distintos, onde percebeu-se uma diminuição de até 80% no consumo total de energia. Em cenários com congestionamento, observou-se um aumento de 10% no tempo de viagem. Já em cenários sem congestionamento o tempo de viagem diminuiu cerca de 2%. A recuperação de energia representa quase 6% da economia total dos veículos elétricos. Além disso, experimentos mostraram que investimentos na eficiência dos veículos elétricos podem resultar em uma economia de até 15% de energia.The search for urban mobility solutions that minimize the aggression to the environment is increasing. Electric vehicles are an attractive alternative because they reduce greenhouse gas emissions, noise pollution, and oil consumption. However, their limited autonomy and the lack of charging stations restrict their popularization. Therefore, government incentive policies have been developed in order to offer benefits to those who choose an electric vehicle. It is estimated that the entire urban fleet will be replaced by these vehicles in a few decades. Therefore, it is important to understand the changes in travel time and energy consumption from the inclusion of electric vehicles in traffic scenarios. Previous works determined these changes by studying the differences between the internal engine of conventional and electric vehicles. However, given the characteristics of the latter, drivers of electric vehicles care about saving energy and may want to choose different routes. Thus, a complete analysis of these impacts should consider a redistribution of traffic. This work proposes a bi-objective traffic assignment method that considers the travel time and the energy consumption to determine the distribution of electric vehicles in urban traffic scenarios. We introduce two strategies for flow distribution as models of route choice. As a procedure of the traffic assignment method, we propose a bi-objective shortest path algorithm for electric vehicles. Our approach was applied to three different scenarios, which resulted in a decrease of up to 80% in total energy consumption. In congested scenarios, we observe an increase of about 10% in average travel time. In uncongested scenarios, travel time decreases about 2%. Energy recovery is almost 6% of the total savings of electric vehicles. Moreover, experiments have shown that investments in the efficiency of electric vehicles can result in up to 15% of energy savings.
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Roy, Didier. "Optimisation et personnalisation des parcours d'apprentissage à l'aide des technologies numériques." Thesis, Paris, CNAM, 2015. http://www.theses.fr/2015CNAM1017/document.
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Depuis le « Plan Informatique Pour Tous » de 1985, les technologies numériques ne cessent d'occuper une place grandissante dans l'enseignement : manuels numériques, logiciels de géométrie dynamique, learning games, e-learning, blended learning, MOOC, classes inversées, robotique éducative, etc.L'ambition de nos travaux est de montrer que certaines de ces technologies peuvent contribuer à améliorer les apprentissages, en dynamisant les contenus, en accentuant la motivation des étudiants, en proposant des dispositifs adaptés à la formation à distance, en personnalisant les parcours pédagogiques.Les enjeux autour de ces questions sont importants. La nécessité de motiver les étudiants et de personnaliser les apprentissages apparaît de plus en plus clairement. Ce sont des atouts majeurs pour lutter contre le décrochage scolaire et pour l'égalité des chances.Objectifs de nos travaux antérieurs à 2011 :— Ludifier et animer des contenus afin de les rendre plus motivants et plus explicites.— Visualiser des concepts en manipulant des objets numériques.— Virtualiser des objets d'apprentissage pour s'affranchir de contraintes matérielles afin de faire travailler des méthodes, de dépasser des difficultés de manipulation et des situations de handicap.— Fournir des outils d'interactivité, de visualisation, de calcul formel et de géométrie pour des environnements informatiques d'apprentissage (plateformes d'enseignement à distance, logiciels).— Fournir des outils de monitoring des activités des utilisateurs afin de suivre au mieux leur progression, afin de pouvoir les suivre au plus près dans leurs cheminements, de leur fournir des retours adaptés et des parcours personnalisés, de les rendre plus autonomes.— Expérimenter des objets à la fois numériques et tangibles tels que les robots pour évaluer leur impact dans les apprentissages.— Repenser les manuels scolaires en les accompagnant de dispositifs numériques.Ces travaux ont trouvé un prolongement ciblé, fortement ancré recherche, dans des travaux plus récents.Objectifs de nos travaux postérieurs à 2011 :— Optimiser et personnaliser en profondeur les apprentissages en faisant appel à l'intelligence artificielle et à des algorithmes de machine learning.— Introduire des objets tangibles, tels que les robots, que les élèves peuvent manipuler, voire programmer, pour éclairer différemment les apprentissages et proposer une approche concrète pour construire de nouveaux conceptsSince the "Plan Informatique Pour Tous" in 1985, digital technologies occupy an increasingly importance in education: digital textbooks, dynamic geometry software, learning games, e-learning, blended learning, MOOC, flipped classrooms, educational robotics, etc.The aim of our work is to show that some of these technologies can contribute to improve learning, boosting learning contents, emphasizing student motivation by proposing devices suitable for distance learning and personalizing learning paths.The stakes of these issues are important. The need to motivate students and personalize learning is more and more crucial. These are major assets to reduce dropout and promote equal opportunities.Objectives of our work before 2011:- Gamify contents to make them more motivating.- Visualize concepts by using digital objects.- Virtualize learning objects in order to reduce physical constraints to work methods, to overcome handling difficulties and disability situations.- Provide tools for interactivity, visualization, computer algebra and geometry for computer environments learning (distance learning platforms, software).- Provide tools for monitoring user activity in order to better track their progress, to follow them with precision, to making them more autonomous.- Experiment with objects both digital and tangible such as robots, to assess their impact in learning.- Build new textbooks by accompanying them with digital devices.This work was continued in recent and more research-driven work.Objectives of our work from 2011:- Optimize and personalize learning by using artificial intelligence and machine learning algorithms.- Use tangible objects such as robots, that students can manipulate and program, to approach learning differently to provide concrete environment to build new concepts
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Nakache, Elie. "Chemin optimal, conception et amélioration de réseaux sous contrainte de distance." Thesis, Aix-Marseille, 2016. http://www.theses.fr/2016AIXM4023/document.
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Cette thèse porte sur différents problèmes d'optimisation combinatoire dont nous avons caractérisé la difficulté en décrivant des réductions et des algorithmes polynomiaux exacts ou approchés.En particulier, nous étudions le problème de trouver, dans un graphe orienté sans cycle dont les sommets sont étiquetés, un chemin qui passe par un maximum d'étiquettes différentes. Nous établissons qu'il n'existe pas d'algorithme polynomial avec un facteur constant pour ce problème. Nous présentons aussi un schéma qui permet d'obtenir, pour tout $epsilon >0$, un algorithme polynomial qui calcule un chemin collectant $ O(OPT^{1-epsilon})$ étiquettes.Nous étudions ensuite des variantes du problème de l'arbre couvrant de poids minimum auquel nous ajoutons des contraintes de distance et d'intermédiarité. Nous prouvons que certaines variantes se résolvent en temps polynomial comme des problèmes de calcul d'un libre de poids minimum commun à deux matroïdes. Pour une autre variante, nous présentons un algorithme d'approximation facteur 2 et nous prouvons qu'il n'existe pas d'algorithme polynomial avec un meilleur facteur constant.Enfin, nous étudions un problème d'améliorations de réseaux du point de vue du partage des coûts. Nous montrons que la fonction de coût associée à ce problème est sous-modulaire et nous utilisons ce résultat pour déduire un mécanisme de partage des coûts qui possède plusieurs bonnes propriétésIn this thesis, we investigate several combinatorial optimization problems and characterize their computational complexity and approximability by providing polynomial reductions and exact or approximation algorithms.In particular, we study the problem of finding, in a vertex-labeled directed acyclic graph, a path collecting a maximum number of distinct labels. We prove that no polynomial time constant factor approximation algorithm exists for this problem. Furthermore, we describe a scheme that produces, for any $epsilon >0$, a polynomial time algorithm that computes a solution collecting $O(OPT^{1-epsilon})$ labels. Then, we study several variants of the minimum cost spanning tree problem that take into account distance and betweenness constraints. We prove that most of these problems can be solved in polynomial time using a reduction to the weighted matroid intersection problem. For an other problem, we give a factor 2 approximation algorithm and prove the optimality of this ratio.Finally, we study a network improvement problem from a cost sharing perspective. We establish that the cost function corresponding to this problem is submodular and use this result to derive a cost sharing mechanism having several good properties
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Abune'meh, Mohammed. "Optimisation de l’aménagement d’un Chantier de Construction en Fonction des Risques Naturels et Technologiques, Utilisation du SIG." Thesis, Paris Est, 2017. http://www.theses.fr/2017PESC1012/document.
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Les chantiers de construction contiennent plusieurs installations. Celles-ci sont susceptibles d’être endommagées par des incidents liés aux risques naturels ou technologiques comme les incendies, les explosions, les ondes de souffles, etc. Ces incidents peuvent avoir des conséquences néfastes sur l’ensemble du processus de construction, ce qui pourrait entrainer des accidents graves ayant un impact majeur sur la productivité des employés, le temps global du projet, sa qualité et son budget. Par conséquent les gestionnaires et les planificateurs du projet doivent adopter et développer des approches novatrices capables de faire face aux risques naturels potentiels, de minimiser leurs conséquences et de faciliter l’évacuation du site en cas de danger. Une de ces approches consiste à optimiser l’aménagement des chantiers de construction. En général, la réduction des dommages résultants de risques naturels ou technologiques est encore un défi scientifique.Dans cette thèse, deux modèles (déterministe et probabiliste) sont développés pour minimiser les risques au sein d’un chantier. La méthode adoptée pour le développement de ces deux modèles consiste en :• La modélisation des éléments du chantier, par exemple : le générateur électrique, les bureaux et les entrepôts de matériaux, sont modélisés en 2D, pour agir en tant que source d’aléa et/ou cible vulnérable potentielle.• La modélisation de l’aléa : elle montre l’interaction des aléas entre les composants du chantier.• La modélisation de la vulnérabilité : elle représente la faiblesse potentielle des cibles sur l’aléa généré par chaque source.• La définition de la fonction d’utilité : elle vise à offrir une disposition optimisée avec un minimum de risque total sur le chantier. L’algorithme à évolution différentielle est adopté pour exécuter le processus d’optimisation.D’une part, dans le modèle déterministe, nous utilisons le principe de la syntaxe spatiale pour étudier l’impact des configurations spatiales dans l’évaluation du risque sur le chantier. Par conséquent, comme le processus d’évacuation est pris en compte dans l’estimation du risque, le risque réel est amplifié en utilisant le facteur de pénalité appelé « profondeur moyenne ». L’algorithme de Dijkstra est appliqué sur un modèle déterministe afin de trouver les chemins les plus sûrs (chemins de moindre risque) pour évacuer les sites à partir de chaque position sur le chantier vers les lieux sûrs afin de diminuer les pertes humaines et matérielles.D’autre part, le modèle probabiliste suppose que le risque est composé de la défaillance individuelle de chaque installation sur le chantier de construction. La simulation numérique est utilisée pour trouver la distribution de probabilités des défaillances pour l’ensemble du site.Les fonctionnalités d’un SIG (Système d’Information Géographique) ont été utilisées pour présenter les données sous forme de cartes, pour produire des cartes spatiales de risque sur le chantier de construction, pour mettre en œuvre l’algorithme de Dijkastra et pour l’analyse du coût le plus faible.A titre indicatif, les modèles proposés sont utilisés dans un cas d’étude comprenant plusieurs installations. Dans le modèle déterministe, toutes ces installations agissent comme des sources d’aléa et des cibles vulnérables, en même temps, dans le modèle probabiliste, quelques-unes de ces installations agissent comme des sources d’aléa et toutes comme des cibles vulnérables. Les résultats obtenus montrent que les modèles proposés sont efficaces en raison de leur capacité à générer une disposition optimale du site avec un environnement de travail plus sûr. En outre, les modèles obtenus sont capables de mettre en évidence les zones les plus risquées d’un chantier, de générer les chemins d’évacuation les moins risqués, ce qui permettra de minimiser les blessures graves et les victimes en cas d’urgenceConstruction sites contain several supporting facilities that are required to complete construction activities. These facilities are susceptible to damage due to the occurrence of natural or technological hazards such as fire, explosion, blast wave, and so on. These may cause adverse consequences for the whole construction process, which in turn lead to fatal accidents that have a major impact on worker and employee productivity, project completion time, project quality and project budget. Therefore, project planners must adopt and develop innovative approaches able to face the occurrence of potential hazards, minimize their consequences, and facilitate the evacuation of the site in case of their occurrence. One of these approaches is optimizing construction site layout. In general, generating construction site layout able minimizing risk resulting from natural or technological hazards is still a scientific challenge.In the present research, two proposed model (deterministic and probabilistic) are developed to minimize the risks within a construction site. The common methodology adopted to develop these two models consists of:• Modeling construction site components, for instance; electric generator, offices and material storages, in a 2D layout, to act as either hazardous source or potential target or both at the same time.• Modeling hazard: it shows the hazard interaction among site components and the attenuation of hazard.• Modeling vulnerability: it represents the potential weakness of whole targets to the hazard generated from each source.• Defining the utility function: it aims to afford an optimized site layout with minimum total risk in the construction site. The differential evolution algorithm is adopted to run optimization process.Particularly, in the deterministic model, we use space syntax principle in order to realize the impact of space configurations in evaluating the risk in the construction site. Therefore, as the evacuation process is considered in estimating the risk, the actual risk is amplified by utilizing penalty factor called mean depth. Furthermore, Dijkstra’s algorithm is run on deterministic model to find the safest paths (least risk paths) for evacuating sites from any position on the construction site towards the safe places in order to diminish losses and fatalities. On the other hand, the framework utilized to develop a probabilistic model assumed that the risk is combined of the individual failure of each facility within a construction site. Moreover, the numerical simulation is performed to find the probabilistic distribution of failure for the whole site.Geographic information system (GIS) capabilities were exploited, in this research, to present data in maps format, generate the spatial risk map in the construction site, and implement the Dijkstra’s algorithm and least-cost path analysis.For illustration purposes, the proposed models are employed in a case study consisting of several facilities. In the deterministic model, all of these facilities act as hazardous sources and potential targets, at the same time, while, in a probabilistic model, only three of these facilities act as fire hazardous sources, whereas, all of them are potential targets. The results revealed that the proposed models are efficient due to their capability of generating site layout with the safer work environment. In addition, the model is capable of highlighting the riskiest areas within a construction site. Moreover, the proposed models are able to generate paths through least-risk zones, which will minimize the serious injuries and victims in cases of emergencies
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Liu, Jianhua. "Contemporary data path design optimization." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2006. http://wwwlib.umi.com/cr/ucsd/fullcit?p3214712.
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Thesis (Ph. D.)--University of California, San Diego, 2006.Title from first page of PDF file (viewed July 10, 2006). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 80-82).
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Feehery, William Francis 1970. "Dynamic optimization with path constraints." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/29879.
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Houacine, Mohamed. "Optimisation de trajectoires pour la réduction du bruit et de la consommation de carburant des avions commerciaux durant les phases d’approche et de décollage." Thesis, Lyon 1, 2012. http://www.theses.fr/2012LYO10031.
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Les bruits et les polluants atmosphériques émis par les avions commerciaux représentent un défi environnemental important, un problème de santé publique et une contrainte économique pour le développement durable du transport aérien. D'un autre côté, le développement économique des régions est intimement lié au secteur du transport aérien. Ce dernier agit comme un multi-capteur économique pour supporter le développement régional et desservir les grands centres. Cette réalité s'explique entre autres par le fait que la mondialisation des marchés impose l'utilisation de moyens rapides et compétitifs pour le transport des voyageurs et des marchandises. Notre approche est une modélisation mathématique du problème de choix des trajectoires de vol dans un domaine continu. La première étape dans la modélisation d'un tel problème est l'écriture des équations qui traduisent la dynamique de vol de l'avion. Ensuite, vient la modélisation est la synthèse des critères d'optimisation. Les critères qu'on a retenus dans notre travail sont la consommation de carburant (critère d'énergie) et le bruit perçu au sol (critère de la gêne occasionnée pour les riverains). En combinant les deux parties "modèle de la dynamique du vol" et "critères d'optimisation", et en intégrant d'autres contraintes liées à la sécurité du vol, on aboutit à un modèle mathématique qui appartient à la classe des problèmes non linéaires de contrôle optimal. C'est une classe difficile de problèmes d'optimisation qui pose un certain nombre de difficultés lors de la construction d'algorithmes de résolution. Pour résoudre le problème ainsi posé, deux approches distinctes peuvent être envisagées : méthodes directes et méthodes indirectes. Nous avons implémenté une méthode dite " pseudo spectrale de Gauss " pour la résolution du problème de contrôle. Le choix de cette méthode est basé sur une propriété très importante et qui garantit l'équivalence entre l'application des deux schémas : direct et indirects. Des résultats sont présentés et discutés. Nos résultats donnent des pistes sur de nouvelles procédures de vol qui minimisent le bruit et la consommation de carburant durant les phases d'atterrissage et de décollage. Par ailleurs, la résolution numérique consolide également le potentiel des approches CDA recommandées par l'OACI. Une comparaison aux procédures standards et une analyse de sensibilité aux critères est présentéeNoise and air pollution from commercial aircraft represent a significant environmental challenge, a public health problem and an economic constraint to the sustainable development of air transport. On the other hand, the economical development of the regions is closely linked to the airline industry. This fact is partly explained by the the globalization of markets that requires the use of fast and competitive means to transport people and goods. We propose a mathematical model to tackle this problem by optimizing flight paths in order to minimize noise emission and fuel consumption. The first step is to express the dynamics of flight of the aircraft. Then comes the synthesis of optimization criteria. The criteria we used in our work are the fuel consumption (criterion of energy) and the perceived noise levels at the ground (criterion of inconvenience for local residents). By combining the two previous parts, and incorporating other constraints related to flight safety, we obtain a mathematical model that belongs to a class of nonlinear optimal control problems. It is a difficult class of optimization problems that raises several difficulties during the construction of solving algorithms. Two different ways can be considered to solve this problem : direct methods and indirect methods. We have developed and implemented a direct method called "Gauss Pseudo-spectral Method" to solve the optimal control problem that we obtained. The choice of this method is based on a very important property that guarantees the equivalence between the use of two schemes : direct and indirect. Results are presented and discussed. Our results provide a new view on flight procedures that minimize noise and fuel consumption during landings and takeoffs. Moreover, the numerical solution also consolidates the potential of CDA approaches which are recommended by ICAO. A comparison with standard procedures and a sensitivity analysis are presented
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Botha, Marlene. "Online traffic engineering for MPLS networks." Thesis, Stellenbosch : Stellenbosch University, 2004. http://hdl.handle.net/10019.1/50049.
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Thesis (MSc) -- Stellenbosch University, 2004.ENGLISH ABSTRACT: The Internet is fast evolving into a commercial platform that carries a mixture of narrow- and broadband applications such as voice, video, and data. Users expect a certain level of guaranteed service from their service providers and consequently the need exists for efficient Internet traffic engineering to enable better Quality of Service (QoS) capabilities. Multi-protocol Label Switching (MPLS) is a label switching protocol that has emerged as an enabling technology to achieve efficient traffic engineering for QoS management in IP networks. The ability of the MPLS protocol to create explicit virtual connections called Label Switched Paths (LSPs) to carry network traffic significantly enhances the traffic engineering capabilities of communication networks. The MPLS protocol supports two options for explicit LSP selection: offline LSP computation using an optimization method and dynamic route selection where a single node makes use of current available network state information in order to compute an explicit LSP online. This thesis investigates various methods for the selection of explicit bandwidth guaranteed LSPs through dynamic route selection. We address the problem of computing a sequence of optimal LSPs where each LSP can carry a specific traffic demand and we assume that no prior information regarding the future traffic demands are available and that the arrival sequence of LSP requests to the network is unknown. Furthermore, we investigate the rerouting abilities of the online LSP selection methods to perform MPLS failure restoration upon link failure. We propose a new online routing framework known as Least Interference Optimization (LIO) that utilizes the current bandwidth availability and traffic flow distribution to achieve efficient traffic engineering. We present the Least Interference Optimization Algorithm (LIOA) that reduces the interference among competing network flows by balancing the number and quantity of flows carried by a link for the setup of bandwidth guaranteed LSPs in MPLS networks. The LIOA routing strategy is evaluated and compared against well-known routing strategies such as the Minimum Hop Algorithm (MHA), Minimum Interference Routing Algorithm (MIRA), Open Shortest Path First (OSPF) and Constraint Shortest Path First (CSPF) by means of simulation. Simulation results revealed that, for the network topologies under consideration, the routing strategies that employed dynamic network state information in their routing decisions (LIOA, CSPF and MIRA) generally outperformed the routing strategies that only rely on static network information (OSPF and MHA). In most simulation experiments the best performance was achieved by the LIOA routing strategy while the MHA performed the worse. Furthermore we observed that the computational complexity of the MIRA routing strategy does not translate into equivalent performance gains. We employed the online routing strategies for MPLS failure recovery upon link failure. In particular we investigated two aspects to determine the efficiency of the routing strategies for MPLS rerouting: the suitability of the LSP configuration that results due to the establishment of LSPs prior to link failure and the ability of the online routing strategy to reroute failed LSPs upon link failure. Simulation results revealed similar rerouting performance for all online routing strategies under investigation, but a LSP configuration most suitable for online rerouting was observed for the LIOA routing strategy.
AFRIKAANSE OPSOMMING:Die Internet is voordurend besig om te evoleer in 'n medium wat 'n wye reeks moderne kommunikasietegnologiee ondersteun, insluitende telefoon, video en data. Internet gebruikers verwag gewaarborgde diens van hul diensverskaffers en daar bestaan dus 'n vraag na doeltreffende televerkeerbeheer vir gewaarborgde Internet diensgehalte. Multiprotokol Etiketskakeling (MPLS) is 'n etiketskakeling protokol wat doeltreffende televerkeerbeheer en diensgehalte moontlik maak deur die eksplisiete seleksie van virtuele konneksies vir die transmissie van netwerkverkeer in Internetprotokol (IP) netwerke. Hierdie virtuele konneksies staan bekend as etiketgeskakelde paaie. Die MPLS protokol ondersteun tans twee moontlikhede vir eksplisiete seleksie van etiketgeskakelde paaie: aflyn padberekening met behulp van optimeringsmetodes en dinamiese aanlyn padseleksie waar 'n gekose node 'n eksplisiete pad bereken deur die huidige stand van die netwerk in ag te neem. In hierdie tesis word verskeie padseleksiemetodes vir die seleksie van eksplisiete bandwydte-gewaarborgde etiketgeskakelde paaie deur mid del van dinamiese padseleksie ondersoek. Die probleem om 'n reeks optimale etiketgeskakelde paaie te bereken wat elk 'n gespesifeerde verkeersaanvraag kan akkommodeer word aangespreek. Daar word aanvaar dat geen informasie in verband met die toekomstige verkeersaanvraag bekend is nie en dat die aankomsvolgorde van etiketgeskakelde pad verso eke onbekend is. Ons ondersoek verder die herroeteringsmoontlikhede van die aanlyn padseleksiemetodes vir MPLS foutrestorasie in die geval van skakelonderbreking. Vir hierdie doel word 'n nuwe aanlyn roeteringsraamwerk naamlik Laagste Inwerking Optimering (LIO) voorgestel. LIO benut die huidige beskikbare bandwydte en verkeersvloeidistribusie van die netwerk om doeltreffende televerkeerbeheer moontlik te maak. Ons beskryf 'n Laagste Inwerking Optimering Algoritme (LIOA) wat die inwerking tussen kompeterende verkeersvloei verminder deur 'n balans te handhaaf tussen die aantal en kwantiteit van die verkeersvloeistrome wat gedra word deur elke netwerkskakel. Die LIOA roeteringstrategie word geevalueer met behulp van simulasie en die resultate word vergelyk met ander bekende roeteringstrategiee insluitende die Minimum Node Algorithme (MHA), die Minimum Inwerking Algoritme (MIRA), die Wydste Kortste Pad Eerste Algoritme (OSPF) en die Beperkte Kortste Pad Eerste Algoritme (CSPF). Die resultate van die simulasie-eksperimente to on dat, vir die netwerk topologiee onder eksperimentasie, die roeteringstratgiee wat roeteringsbesluite op dinamiese netwerk informasie baseer (LIOA, MIRA, CSPF) oor die algemeen beter vaar as die wat slegs staatmaak op statiese netwerkinformasie (MHA, OSPF). In die meeste simulasie-eksperimente vaar die LIOA roeteringstrategie die beste en die MHA roeteringstrategie die slegste. Daar word verder waargeneem dat die komputasiekomplesiteit van die MIRA roeteringstrategie nie noodwendig weerspieel word in die sukses van roeteringsuitkoms nie. In die geval waar die aanlyn roeteringstrategiee aangewend word vir MPLS foutrestorasie, toon die resultate van simulasie-eksperimente dat al die roeteringstrategiee min of meer dieselfde uitkoms lewer ten opsigte van herroetering van onderbreekte verkeersvloei. Die konfigurasie van etiketgeskakelde paaie deur die LIOA roeteringstrategie voor skakelonderbreking is egter die geskikste vir televerkeer herroetering na skakelonderbreking
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Merle, Dorothée. "Flight path optimization for an airplane." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for energi- og prosessteknikk, 2011. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-13261.
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The diminution of the fuel consumption during the flight trajectory has an impact on the cost of the travel and answers to the ecologic challenge Green Sky. The analysis has for objective to optimize the flight trajectory of the aircraft in order to reduce the fuel consumption. The flight trajectory is defined by a simplified description and depends on some parameters which affect the different phases of the trajectory. The flight description is introduced in a computer code and the different parameters vary in order to define their influence on the fuel consumption. The results which are obtained show the influence of the times of climb and descent and the cruise altitude on the fuel consumption. The variation according to the defined configuration is in the order of few percent. Today, all the few kilograms of fuel which are saved are important. The different phases of the flight trajectory have to be optimized to reduce the fuel consumption.
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Liu, Zheng 1962. "Optimization of spherical four-bar path generators." Thesis, McGill University, 1988. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=61814.
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Sridharan, Vidhumana. "Enterprise network convergence : path to cost optimization /." Online version of thesis, 2007. http://hdl.handle.net/1850/4393.
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Ramanata, Peeroon Pete. "Optimal Vehicle Path Generator Using Optimization Methods." Thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/36615.
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This research explores the idea of developing an optimal
path generator that can be used in conjunction with a
feedback steering controller to automate track testing
experiment. This study specifically concentrates on
applying optimization concepts to generate paths that
meet two separate objective functions; minimum time and
maximum tire forces.
A three-degree-of freedom vehicle model is used to approximate the handling dynamics of the vehicle. Inputs into the vehicle model are steering angle and longitudinal force at the tire. These two variables approximate two requirements that are essential in operating a vehicle. The Third order Runge-Kutta integration routine is used to integrate vehicle dynamics equations of motion. The Optimization Toolbox of Matlab is used to evaluate the optimization algorithm. The vehicle is constrained with a series of conditions, includes, a travel within the boundaries of the track, traction force limitations at the tire, vehicle speed, and steering.
The simulation results show that the optimization applied to vehicle dynamics can be useful in designing an automated track testing system. The optimal path generator can be used to develop meaningful test paths on existing test tracks. This study can be used to generate an accelerated tire wear test path, perform parametric study of suspension geometry design using vehicle dynamics handling test data, and to increase repeatability in generating track testing results.
Vita removed at author's request. GMc 3/13/2013
Master of Science
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Marehalli, Jayavardhan N. "Assembly Sequence Optimization and Assembly Path Planning." Thesis, Virginia Tech, 1999. http://hdl.handle.net/10919/44837.
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This thesis addresses two important aspects of automatic assembly viz., assembly sequence planning and assembly path planning. These issues are addressed separately starting with sequence planning followed by assembly path planning.
For efficient assembly without feedback systems (or, passive assembly), an assembler should know the ideal orientation of each component and the order in which to put the parts together (or, assembly sequence). A heuristic is presented to find the optimal assembly sequence and prescribe the orientation of the components for a minimum set of grippers = ideally one. The heuristic utilizes an index of difficulty (ID) that quantifies assembly. The ID for each task in the assembly process is computed on the basis of a number of geometrical and operational properties. The objective of the optimization problem here is to minimize the assembly ID and categorize parts/subassemblies based on their preferred direction of assembly while allowing re-orientation of the base part. It is assumed that the preferred direction of assembly is vertically downward, consistent with manual as well as most automatic assembly protocols. Our attempt is to minimize the number of degrees of freedom required in a re-orienting fixture and derive the requirements for such a fixture. The assembly of a small engine is used as an example in this study due to the variety of ideally rigid parts involved.
In high precision assembly tasks, contact motion is common and often desirable. This entails a careful study of contact states of the parts being assembled. Recognition of contact states is crucial in planning and executing contact motion plans due to inevitable uncertainties. Dr. Jing Xiao of UNCC introduced the concept of principal contacts (PC) and contact formation (CF) for contact state recognition. The concept of using CFs (as sets of PCs) has the inherent advantage that a change of CF is often coincident with a discontinuity of the general contact force (force and torque). Previous work in contact motion planning has shown that contact information at the level of PCs along with the sensed location and force information is often sufficient for planning high precision assembly operations. In this thesis, we present results from experiments involving planned contact motions to validate the notion of PCs and CFs -- an abrupt change in general contact force often accompanies a change between CFs. We are only concerned with solving the 2D peg-in-corner problem.Master of Science
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Olsson, Per-Magnus. "Methods for Network Optimization and Parallel Derivative-free Optimization." Doctoral thesis, Linköpings universitet, Optimeringslära, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-104110.
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This thesis is divided into two parts that each is concerned with a specific problem. The problem under consideration in the first part is to find suitable graph representations, abstractions, cost measures and algorithms for calculating placements of unmanned aerial vehicles (UAVs) such that they can keep one or several static targets under constant surveillance. Each target is kept under surveillance by a surveillance UAV, which transmits information, typically real time video, to a relay UAV. The role of the relay UAV is to retransmit the information to another relay UAV, which retransmits it again to yet another UAV. This chain of retransmission continues until the information eventually reaches an operator at a base station. When there is a single target, then all Pareto-optimal solutions, i.e. all relevant compromises between quality and the number of UAVs required, can be found using an efficient new algorithm. If there are several targets, the problem becomes a variant of the Steiner tree problem and to solve this problem we adapt an existing algorithm to find an initial tree. Once it is found, we can further improve it using a new algorithm presentedin this thesis. The second problem is optimization of time-consuming problems where the objective function is seen as a black box, where the input parameters are sent and a function valueis returned. This has the important implication that no gradient or Hessian information is available. Such problems are common when simulators are used to perform advanced calculations such as crash test simulations of cars, dynamic multibody simulations etc. It is common that a single function evaluation takes several hours. Algorithms for solving such problems can be broadly divided into direct search algorithms and model building algorithms. The first kind evaluates the objective function directly, whereas the second kind builds a model of the objective function, which is then optimized in order to find a new point where it is believed that objective function has agood value. Then the objective function is evaluated in that point. Since the objective function is very time-consuming, it is common to focus on minimizing the number of function evaluations. However, this completely disregards the possibility to perform calculations in parallel and to exploit this we investigate different ways parallelization can be used in model-building algorithms. Some of the ways to do this is to use several starting points, generate several new points in each iteration, new ways of predicting a point’s value and more. We have implemented the parallel extensions in one of the state of the art algorithms for derivative-free optimization and report results from testing on synthetic benchmarksas well as from solving real industrial problems.
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Fung, Sze-tat, and 馮思達. "Learning path optimization with incomplete learning object metadata." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B47169850.
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One of the fundamental concerns of instructional design is pedagogical sequencing which is a practice of organizing course materials according to the underlying knowledge structure and concept dependency. In the conventional settings, like the secondary schools or tertiary institution, instructors are required to interpret learning materials by their own domain knowledge. But in many online learning systems, analyzing and interpreting learning materials are very challenging due to the lack of instructional contexts and pedagogical attributes of the learning units.
The learning objects and learning object metadata (LOM) are learning technologies to formalize the concept of learning unit and standardizing the specification of learning object annotation framework. The learning object is aimed to provide a solution for reuse and sharing of learning materials, and to provide infrastructure for pedagogical design. The LOM has been widely adopted in various learning systems, methodologies and system frameworks proposed to solve instructional design problem based on the pedagogical information as provided in the LOM. However, an empirical study showed that most real-life learning objects do not provide necessary pedagogical information. Thus, it is not clear how the issue of incomplete metadata and hence incomplete pedagogical information will affect those LOM based methods.
A new approach to reconstruct the underlying knowledge structure based on information extracted from LOM and data mining techniques is proposed. The main idea of the approach is to reconstruct knowledge structure by the context of learning materials. Intrinsically, the vector space model and the k-means clustering algorithm are applied to reconstruct the knowledge graph based on keyword extraction techniques, and concept dependency relations are extracted from the obtained knowledge graph. Then, the genetic algorithm is applied to optimize for a learning path that satisfies most of the obtained concept dependencies. Furthermore, the performance of applying different semantic interpreters and rule extraction methodology are carefully tested and compared. Experimental results revealed that learning paths generated by the proposed approach are very similar to learning paths designed by human instructors.published_or_final_version
Electrical and Electronic Engineering
Master
Master of Philosophy
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Khoury, Nancy. "Path enumeration & redundancy removal for timing optimization." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2009. http://wwwlib.umi.com/cr/syr/main.
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Gough, William Dennis. "Automated Flow Path Design Optimization Using Mesh Morphing." BYU ScholarsArchive, 2011. https://scholarsarchive.byu.edu/etd/2843.
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The use of CAD models and CFD analysis has become an essential part of fluid flow design. To reduce the time spent determining a design, optimization frameworks have been implemented to automate the process. Mesh morphing has been implemented within these frameworks to further reduce the time needed. While optimization methods have been developed to optimize a fluid flow path, the optimum design needs to be recreated in a CAD model. A method has been developed which eliminates the need to recreate the optimal results in CAD. This is accomplished by using mesh morphing, CAD and CFD together in an optimization framework. The method developed has been implemented with a significant time savings over the use of a traditional meshing optimization framework.
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Schell, Kevin E. "Virtual pooling approximation using longest path network optimization." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/118702.
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Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018.Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 94-95).
Abstract This thesis proposes a network swapping mechanism to approximate a virtual finished goods inventory pool under the constraint of fragmented commercial channel ownership. Globally, Caterpillar sells its product through a network of independently owned dealers which own their equipment inventory. These dealers are selling a product which has significant configuration complexity, a high coefficient of variation in demand, and long factory lead times - these three factors conspire to create a situation in which dealers must either maintain high levels of on-hand inventory or sacrifice customer service level. Virtual pooling can be a powerful technique for reducing held inventory and improving customer service level. In such a system, physical inventory is maintained in multiple locations, but a strong transshipment network allows inventory to be continuously rebalanced and effectively managed as a single pool. At Caterpillar, however, this is constrained by the fact that dealers are unwilling to unilaterally give up equipment that they own and which represents a potential sale, even if that equipment could be more effectively used by another dealer. This thesis proposes that a robust dealer swapping network that allows for multilateral swaps can generate universally beneficial inventory movement which lowers inventory and accelerates sales across the network. The mathematical formulation of this problem involves solving a longest path problem over a suitably defined network. In order to demonstrate the efficacy of this technique, a commercial network model was developed which allows for the simulation of multi-period equipment ordering, inventory management, and sales across a sample dealer network with and without network swapping implemented. Baseline simulation results conducted for a single vehicle class (Medium Wheel Loaders) suggest that network swapping has the potential to reduce on-hand inventory by more than 12% and decrease customer back orders by more than 17%. The swapping mechanism yields an NPV uplift of approximately USD 3 to 4M to the dealer network. This thesis concludes by proposing important extensions of the work conducted in this thesis to improve the practicality and financial impact of the proposed network swapping system.
by Kevin E. Schell.
S.M.
M.B.A.
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Rinehart, Michael David. "The value of information in shortest path optimization/." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/58452.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 92-93).
Information about a random event (termed the source) is typically treated as a (possibly noisy) function of that event. Information has a destination, an agent, that uses the information to make a decision. In traditional communication systems design, it is usually assumed that the agent uses the information to produce an estimate of the source, and that estimate is in turn used to make the decision. Consequently, the typical objective of communication-systems design is to construct the communication system so that the joint distribution between the source and the information is "optimal" in the sense that it minimizes the average error of the estimate. Due to resource limitations such as cost, power, or time, estimation quality is constrained in the sense that the set of allowable joint distribution is bounded in mutual information. In the context of an agent using information to make decisions, however, such metrics may not be appropriate. In particular, the true value of information is determined by how it impacts the average payoff of the agent's decisions, not its estimation accuracy. To this end, mutual information may not the most convenient measure of information quantity since its relationship to decision quality may be very complicated, making it difficult to develop algorithms for information optimization. In this thesis, we study the value of information in an instance of an uncertain decision framework: shortest path optimization on a graph with random edge weights.
(cont.) Specifically, we consider an agent that seeks to traverse the shortest path of a graph subject to some side information it receives about the edge weights in advance of and during its travel. In this setting, decision quality is determined by the average length of the paths the agent chooses, not how often the agent decodes the optimal path. For this application, we define and quantify a notion of information that is compatible with this problem, bound the performance of the agent subject to a bound on the amount of information available to it, study the impact of spreading information sequentially over partial decisions, and provide algorithms for information optimization. Meaningful, analytic performance bounds and practical algorithms for information optimization are obtained by leveraging a new type of geometric graph reduction for shortest path optimization as well as an abstraction of the geometry of sequential decision making.
by Michael David Rinehart.
Ph.D.
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Singh, Daljeet. "Path Planning and Evolutionary Optimization of Wheeled Robots." Cleveland State University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=csu1375744528.
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Murphey, Robert A. "Integrated assignment and path planning." [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0010051.
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Hojnacki, Susan M. "Optimizing algorithms for shortest path analysis /." Online version of thesis, 1991. http://hdl.handle.net/1850/11143.
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Hong, Chyi-Fu. "O(n) planar network shortest path algorithm." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/24841.
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Boen, Gilbert E. "Application of approximation techniques to helicopter flight path optimization." Thesis, Georgia Institute of Technology, 1987. http://hdl.handle.net/1853/13036.
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Streckfuß, Martin [Verfasser]. "Conditional Variational Analysis and Path-dependent Optimization / Martin Streckfuß." Konstanz : KOPS Universität Konstanz, 2019. http://d-nb.info/1182901425/34.
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Almeida, Lucas Assunção de. "Optimization algorithms for the restricted robust shortest path problem." Universidade Federal de Minas Gerais, 2015. http://hdl.handle.net/1843/ESBF-9W2MCJ.
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This dissertation introduces the Restricted Robust Shortest Path problem (R-RSP), a robust optimization version of the Restricted Shortest Path problem (R-SP), a classical NP-hard problem. Given a digraph G, we associate a cost interval and a resource consumption value with each arc of G. R-RSP aims at nding a path from an origin to a destination vertices in G that satises a resource consumption constraint and minimizes a robust optimization criterion, called restricted robustness cost. This problem has practical applications, as routing electrical vehicles in urban areas, when one looks for a path from a location to another taking into account trac jams and the vehicles' autonomy. R-RSP belongs to a new class of problems composed by robust optimization problems whose classical versions (i.e., parameters known in advance) are already NP-hard. We refer to this class as robust-hard problems. Problems in this class are particularly challenging, as solely evaluating the cost of a solution requires solving a NP-hard problem, which corresponds to the classical counterpart of the problem considered. In this study, we discuss some theoretical aspects of R-RSP, including its computational complexity. Indeed, we show that both R-RSP and its decision version are NP-hard. We also derive a MILP formulation (with a polynomial number of variables and an exponential number of constraints) for R-RSP. Based on this formulation, we propose a heuristic method for R-RSP that consists in solving an approximate compact MILP formulation that uses dual information of the linear relaxation of R-SP. Moreover, a Benders-like decomposition approach is proposed to solve R-RSP at optimality. We also present some techniques to improve the convergence speed of the method by providing initial bounds, as well as by generating additional Benders cuts. Computational experiments show the eectiveness of the proposed algorithms. We highlight that the procedures to solve R-RSP presented in this dissertation are not limited to the referred problem, as they can be extended to other robust-hard problems.Introduzimos o problema do caminho mais curto restrito robusto (R-RSP, do inglês restricted robust shortest path problem ), uma versão de otimização robusta do problema do caminho mais curto restrito (R-SP, do inglês restricted shortest path problem ), um clássico problema NP-difícil. Dado um grafo orientado G, associamos um intervalo de custo e um valor de recurso a cada arco de G. R-RSP visa encontrar um caminho de menor custo de um vértice de origem a um de destino em G que satisfaz uma restrição de consumo máximo de recurso e minimiza um critério de otimização robusta, chamado de desvio robusto restrito. R-RSP tem aplicacões práticas, como em roteamento de veículos elétricos em áreas urbanas, quando se procura um caminho de uma localiza- ção a outra levando em consideração engarrafamentos e a autonomia energética do veículo. R-RSP pertence a uma nova classe de problemas composta por problemas de otimização robusta cujas versões de otimização clássica já são NP-difícil. Referimo-nos a essa classe como problemas robusto-difícil. Problemas nessa classe são particularmente desaadores, uma vez que calcular o custo de uma solução envolve resolver um problema NP-difícil, que corresponde à versão clássica do problema considerado. Neste estudo, discutimos aspectos teóricos de R-RSP, incluindo sua complexidade computational. De fato, mostramos que tanto R-RSP como sua versão de decisão são NP-difícil. Derivamos uma formulação de programação inteira mista (com um número polinomial de variáveis e um número exponencial de restrições) para R-RSP. Baseando-nos nessa formulação, propomos uma heurística para R-RSP que consiste em resolver uma formula ção de programação inteira mista que usa informação dual da relaxação linear de R-SP. Propomos ainda uma estratégia baseada em decomposição de Benders para resolver R-RSP na otimalidade. Apresentamos algumas técnicas para melhorar a velocidade de convergência do método a partir da obtenção de limites iniciais e da geração de cortes de Benders adicionais. Experimentos computacionais mostram a ecácia dos algoritmos propostos. Destacamos que os procedimentos para resolver R-RSP apresentados nesta dissertação não se limitam ao referido problema, já que eles podem ser estendidos a outros problemas robusto-difícil.
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Ur-Rehman, Raza. "Multiobjective optimization of parallel robots and optimal path placement." Ecole centrale de Nantes, 2009. https://hal.archives-ouvertes.fr/tel-01390055.
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Les machines à cinématique parallèle (PKMs en anglais) attirent l'attention de nombreux chercheurs puisqu’elles présentent notamment les avantages suivants :vitesses élevées, bonne précision, faibles inerties et raideur structurelle élevée. Plusieurs machines outils d’architecture innovante sont présentées dans la littérature mais leur utilisation nécessite une analyse approfondie de leurs structure, cinématique et dynamique. Les techniques habituelles de conception peuvent être utilisées pour la conception des PKMs en considérant de manière sommaire des contraintes cinématiques. Un ensemble de solutions non-dominées, appelé ensemble de solutions Pareto optimales, peut être obtenu au moyen de la résolution d’un problème d’optimisation multi-objectif dans lequel les fonctions objectives sont généralement antagonistes. Cela nous permet également de mieux cerner les problèmes de conception complexes. Trois parties distinctes avec comme fil directeur l’optimisation de manipulateurs parallèles sont présentées dans cette thèse. La première partie présente un problème d'optimisation multi-objectif pour la synthèse dimensionnelle de manipulateurs parallèles. Il s’agit de déterminer les paramètres géométriques et structuraux optimaux. L'approche proposée est appliquée à la conception optimale d’un manipulateur parallèle planaire à trois degrés de liberté. La deuxième partie illustre une méthodologie pour le choix des actionneurs de manipulateurs parallèles à l’aide de leurs modèles cinématique et dynamique. Ce travail est réalisé sur la base de l'analyse cinématique et dynamique de l'Orthoglide 5-axes, une machine d’architecture parallèle spatiale dédiée aux opérations d’usinage à grande vitesse conçue à l’IRCCyN. L'analyse est effectuée dans un premier temps pour le poignet sphérique à deux degrés de liberté (ddl) del'Orthoglide 5 axes et ensuite pour le module parallèle de translation, l’Orthoglide 3-axes. Des trajectoires test sont utilisées pour analyser les résultats et une procédure de sélection des moteurs est proposée. La troisième partie de ce mémoire porte sur le placement optimal de trajectoires pour un manipulateur parallèle. Deux problèmes d’optimisation mono et multi-objectifs sont ainsi formulés. Les fonctions objectives de ces problèmes sont : la consommation d'énergie, les couples actionneurs et les sollicitations dynamiques. Une méthode est proposée pourdéterminer le placement optimal d’une trajectoire dans l'espace de travail d'une PKM afin d'optimiser les fonctions objectives précédentes soumises à des contraintes géométriques, cinématiques et dynamiques. La méthodologie proposée est appliquée à l'Orthoglide 3-axes à titre d'exempleParallel Kinematics Machines (PKMs) have attracted attention for their high speed, good accuracy, low mass/inertia properties and high structural stiffness. They are attractive for the innovative machine-tool architectures. However, practicalutilizations for the potential benefits require an extensive and efficient analysis of their structure, kinematics and dynamics. Conventional design techniques may be used for a trivial design of PKMs with a limited capability of considering the performance measures and constraints. A multiobjective optimization approach, on the other hand, can be used to consider a set of optimal trade-off solutions (called Pareto set) between the conflicting design objectives, to better understand the complex design problems. Three separate but inter-linked design optimization issues of parallel manipulators are addressed in this dissertation. Firstly, a multiobjective optimization problem is proposed for the dimensional synthesis of parallel manipulators, in order to determine their optimum structural and geometric parameters. The proposed approach is applied to the optimum design of a three-degree-of-freedom planar parallel manipulator. Secondly, the issue of the actuators selection based on the kinematic and dynamic models of the manipulators is discussed. The process focuses on the kinematic and dynamic analysis of the Orthoglide 5-axis, a spatial PKM developed for high speed operations. The analysis is carried out firstly for the 2-DOF spherical wrist of the Orthoglide 5-axis and then for the 3-DOF translational parallel manipulator, the Orthoglide 3-axis. Some test trajectories are used to analyze the results and a procedure for motors selection is proposed. The last part deals with the optimal path placement of parallel manipulators. Mono- and multi-objective path placement optimization problems for PKMs based on energy consumption, actuators torques and shaking forces are introduced. Accordingly, a methodology is provided to determine the optimal location of a given test path withinthe workspace of a PKM to optimize some objective functions subject to the geometric, kinematic and dynamic constraints of the PKM. The proposed methodology is applied to the Orthoglide 3-axis as an illustrative example
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Hung, Cheng-Huang. "On the inverse shortest path length problem." Diss., Available online, Georgia Institute of Technology, 2004:, 2003. http://etd.gatech.edu/theses/available/etd-04082004-180237/unrestricted/hung%5Fcheng-huang%5F200312%5Fphd.pdf.
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Blouin, Charles. "Trajectory Optimization of a Small Airship." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/33166.
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Pseudo-spectral optimal solvers are used to optimize numerically a performance index of a dynamical system with differential constraints. Although these solvers are commonly used for space vehicles and space launchers for trajectory optimization, few experimental papers exist on optimal control of small airships. The objective of this thesis is to evaluate the use of a pseudo-spectral optimal control solver for generating dynamically constrained, minimal time trajectories. A dynamical model of a small airship is presented, with its experimental virtual mass, drag and motor experimentally modeled. The problems are solved in PSOPT, a pseudo-spectral optimal control code. Experimental tests with a small scale model are performed to evaluate the generated paths. Although drift occurs, as a consequence of an open loop control, the vehicle is capable of following the path. This results of this thesis may find uses in verifying how close to optimal discreet path planners are, to plan complex trajectories on short distances, or to generate dynamic maneuverer such as take-off or landing. Ultimately, improving path planning of small airships will improve their safety, maneuverability and flight-time, which makes them fit for scientific monitoring, for search and rescue, or as mobile telecommunications platforms.
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Nune, Rakesh. "Path Prediction and Path Diversion Identifying Methodologies for Hazardous Materials Transported by Malicious Entities." Thesis, Virginia Tech, 2007. http://hdl.handle.net/10919/36238.
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Safe and secure transportation of hazardous materials (hazmat) is a challenging issue in terms of optimizing risk to society and simultaneously making the shipment delivery economical. The most important safety concern of hazardous material transportation is accidents causing multiple causalities. The potential risk to society from hazmat transportation has led to the evolution of a new threat from terrorism. Malicious entities can turn hazmat vehicles into weapons causing explosions in high profile locations.
The present research is divided into two parts. First, a neural network model is developed to identify when a hazmat truck deviates from its pre-specified path based on its location in the road network. The model identifies abnormal diversions in hazmat carriersâ paths considering normal diversions arising due to incidents. The second part of this thesis develops a methodology for predicting different paths that could be taken by malicious entities heading towards a target after successfully hijacking a hazmat vehicle. The path prediction methodology and the neural network methodology are implemented on the network between Baltimore, Maryland and Washington, DC.
The trained neural network model classified nodes in the network with a satisfactory performance .The path prediction algorithm was used to calculate the paths to two targets located at the International Dulles Airport and the National Mall in Washington, DC. Based on this research, the neural network methodology is a promising technology for detecting a hijacked vehicle in its initial stages of diversion from its pre-specified path. Possible paths to potential targets are plotted and points of overlap among paths are identified. Overlaps are critical locations where extra security measures can be taken for preventing destruction. Thus, integrating both models gives a comprehensive methodology for detecting the initial diversion and then predicting the possible paths of malicious entities towards targets and could provide an important tool for law enforcement agencies minimizing catastrophic events.Master of Science
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Kucuk, Ali. "The Multi - Objective Path Placement Optimization Of Parallel Kinematic Machines." Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615533/index.pdf.
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The aim of this study is to obtain optimal position and orientation of a trajectory frame with respect to the fixed frame of the manipulator. The work path which is given in the trajectory frame is also constrained in the workspace of the 3 &ndashPRS parallel kinematic machine. In the analysis, forward and inverse kinematics solutions are derived as well as the inverse dynamics model using Lagrange&rsquo
s Method. Several algorithms governing the motion of the manipulator are developed. Moreover, optimization goals are defined and evaluated with the genetic algorithm.
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Baumgarten, Peter B. "Optimization of United States Marine Corps Officer Career Path Selection." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2000. http://handle.dtic.mil/100.2/ADA381837.
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Thesis (M.S. in Operations Research) Naval Postgraduate School, September 2000.Thesis advisor, Siriphong Lawphongpanich. "September 200." Includes bibliographical references (p. 67). Also available online.
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Sato, Hiroyuki. "Path optimization for single and multiple searchers: models and algorithms." Monterey, California. Naval Postgraduate School, 2008. http://hdl.handle.net/10945/10380.
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We develop models and solution methodologies to solve the discrete-time path-optimization problem where a single or multiple searchers look for a moving target in a finite set of cells. The single searcher is constrained by maximum limits on the consumption of several resources such as time, fuel, and risk along any path. We develop a specialized branch-and-bound algorithm for this problem that utilizes several new network reduction procedures as well as new bounding technique based on Lagrangian relaxation and network expansion. The resulting algorithm is quite efficient and promising. For the multiple searchers, an optimal set of paths (search plan) is determined by taking advantage of the cooperative search effect. We present a new exact algorithm and two new heuristics to find an optimal or near-optimal search plan. One of the heuristics is based on the cross-entropy method and is found to perform well for a broad range of problem instances. The exact algorithm deals with the specific case of homogeneous searchers and is based on outer approximations by several new cutting planes. In addition, we prove that under certain assumptions the path-optimization problem becomes equivalent to a large-scale linear mixed-integer program.
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Sato, Horiyuki. "Path optimization for single and multiple searchers models and algorithms /." Monterey, Calif. : Naval Postgraduate School, 2008. http://edocs.nps.edu/npspubs/scholarly/theses/2008/Sept/08Sep%5FSato%5FPhD.pdf.
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Dissertation (Ph.D. in Operations Research)--Naval Postgraduate School, September 2008.Dissertation Supervisor(s): Royset, Johannes O. "September 2008." Description based on title screen as viewed on November 4, 2008. Includes bibliographical references (p. 115-119). Also available in print.
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Whiting, James K. (James Kalani) 1980. "Path optimization using sub-Riemannian manifolds with applications to astrodynamics." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/63035.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2011.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 131).
Differential geometry provides mechanisms for finding shortest paths in metric spaces. This work describes a procedure for creating a metric space from a path optimization problem description so that the formalism of differential geometry can be applied to find the optimal paths. Most path optimization problems will generate a sub-Riemannian manifold. This work describes an algorithm which approximates a sub-Riemannian manifold as a Riemannian manifold using a penalty metric so that Riemannian geodesic solvers can be used to find the solutions to the path optimization problem. This new method for solving path optimization problems shows promise to be faster than other methods, in part because it can easily run on parallel processing units. It also provides some geometrical insights into path optimization problems which could provide a new way to categorize path optimization problems. Some simple path optimization problems are described to provide an understandable example of how the method works and an application to astrodynamics is also given.
by James K. Whiting.
Ph.D.
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Rostiti, Cristian. "Automotive Engine Air Path Optimization using Dynamic Inverse Model Allocation." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu157470436430993.
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