Дисертації з теми "Objectifs de parité"
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Sérée, Bastien. "Problèmes d'optimisation des les graphes paramétrés." Electronic Thesis or Diss., Ecole centrale de Nantes, 2022. http://www.theses.fr/2022ECDN0066.
Повний текст джерелаWe are considering weighted oriented graphs with parametrized energy. Firstly we propose an algorithm that, given a graph and one of its vertices, returns trees, every tree representing shortest-paths from the source to every other vertex for a particular zone of the parameter space. Moreover, union of these zones is a covering of the parameter space. Then we consider reachability in graphs with multi-dimensional energy, with stricter constraints that enforce the energy to stay between bounds. We prove decidabilty and complexity of this problem regardless of the dimension and the number of parameters when parameters take integer values. We alsoprove the undecidability of this problem when there is at least one parameter and the dimension is at least two. Finally we study paritygames on parametrized graphs with one and two players whose objective is the conjunction of a qualitative condition on the parity andquantitative one : energy must stay positive. We show the decidability and prove bounds on the complexity of the problem of searchinga winning strategy in both cases with one and two players
Ismaïli, Anisse. "Algorithms for Nash-equilibria in Agent Networks and for Pareto-efficiency in State Space Search : Generalizations to Pareto-Nash in Multiple Objective Games." Thesis, Paris 6, 2016. http://www.theses.fr/2016PA066148.
Повний текст джерелаAn agent is an entity that decides an action. By using this abstraction, it is possible to model two children playing rock-paper-scissors, a software computing a shortest path on the internet for packet-routing on congest numerical networks, as well as an automatic combinatorial auction that sells commercial links in order to make google earn billions. The researchers in algorithmic decision theory and algorithmic game theory (mathematicians and computer scientists) like to think that these real-life examples can be modelled by mean of agents in an interaction decision system, no matter how complex is reality. The modern interactive decision systems find their complexity in multiple aspects. Firstly, the preferences of an agent can be complex to model with real numbers when there are multiple conflicting objectives resulting from every decision. Secondly, the interactions between agents are such that the payoff of every individual depends of the actions of all, making difficult the prediction of the resulting action-profile. This thesis aims at pursuing research efforts lead on these two sources of complexity, in order to consider ultimately both aspects in the same model
Rohling, Gregory Allen. "Multiple Objective Evolutionary Algorithms for Independent, Computationally Expensive Objectives." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/4835.
Повний текст джерелаTeo, Jason T. W. Information Technology & Electrical Engineering Australian Defence Force Academy UNSW. "Pareto multi-objective evolution of legged embodied organisms." Awarded by:University of New South Wales - Australian Defence Force Academy. School of Information Technology and Electrical Engineering, 2003. http://handle.unsw.edu.au/1959.4/38682.
Повний текст джерелаRibeiro, Marco Tulio Correia. "Multi-objective pareto-efficient algorithms for recommender systems." Universidade Federal de Minas Gerais, 2013. http://hdl.handle.net/1843/ESSA-9CHG5H.
Повний текст джерелаSistemas de recomendação tem se tornado cada vez mais populares em aplicações como e-commerce, mídias sociais e provedores de conteúdo. Esses sistemas agem como mecanismos para lidar com o problema da sobrecarga de informação. Uma tarefa comum em sistemas de recomendação é a de ordenar um conjunto de itens, de forma que os itens no topo da lista sejam de interesse para os usuários. O conceito de interesse pode ser medido observando a acurácia, novidade e diversidade dos itens sugeridos. Geralmente, o objetivo de um sistema de recomendação é gerar listas ordenadas de forma a otimizar uma dessas métricas. Um problema mais difícil é tentar otimizar as três métricas (ou objetivos) simultaneamente, o que pode levar ao caso onde a tentativa de melhorar em uma das métricas pode piorar o resultado nas outras métricas. Neste trabalho, propomos novas abordagens para sistemas de recomendaççao multi-objetivo, baseadas no conceito de Eficiência de Pareto -- um estado obtido quando o sistema é de tal forma que não há como melhorar em algum objetivo sem piorar em outro objetivo. Dado que os algoritmos de recomendação existentes diferem em termos de acurácia, diversidade e novidade, exploramos o conceito de Eficiência de Pareto de duas formas distintas: (i) agregando listas ordenadas produzidas por algoritmos existentes de forma a obter uma lista única - abordagem que chamamos de ranking Pareto-eficiente, e (ii), a combinação linear ponderada de algoritmos existentes, resultado em um híbrido, abordagem que chamamos de hibridização Pareto-eficiente. Nossa avaliação envolve duas aplicações reais: recomendação de música com feedback implícito (i.e., Last.fm) e recomendação de filmes com feedback explícito (i.e., Movielens). Nós mostramos que as abordagens Pareto-eficientes são efetivas em recomendar items com bons niveis de acurácia, novidade e diversidade (simultaneamente), ou uma das métricas sem piorar as outras. Além disso, para a hibridização Pareto-eficiente, provemos uma forma de ajustar o compromisso entre acurácia, novidade e diversidade, de forma que a ênfase da recomendação possa ser ajustada dinamicamente para usuários diferentes.
Nordström, Peter. "Multi-objective optimization and Pareto navigation for voyage planning." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-220338.
Повний текст джерелаZeng, Rong-Qiang. "Métaheuristiques multi-objectif basées sur des voisinages pour l'approximation d'ensembles de pareto." Angers, 2012. http://www.theses.fr/2012ANGE0054.
Повний текст джерелаMulti-objective optimization has received more and more attention in the late twenty years. The aim is to generate a Pareto optimal set, which keeps the best compromise among all the objectives. Since it is not possible to compute the Pareto optimal set in a reasonable time in most cases, many multi-objective metaheuristics have been established to approximate the Pareto optimal set. This thesis is devoted to developing metaheuristics to tackle multi-objective optimization problems in general. In order to solve these multi-objective optimization problems, we propose the Hypervolume-Based Multi-Objective Local Search algorithm (HBMOLS). This algorithm uses a hypervolume contribution indicator as the selection measure to compare and select solutions during the search process. Afterwards, we integrate path relinking techniques into the HBMOLS algorithm as a function which initializes new populations for HBMOLS. Then, we present and evaluate different versions of multi-objective hybrid path linking algorithm. To evaluate the efficiency and the generality of our approaches, we carry out experiments on a multi-objective flow shop problem and a multi-objective quadratic assignment problem
Zhong, Hongliang. "Bandit feedback in Classification and Multi-objective Optimization." Thesis, Ecole centrale de Marseille, 2016. http://www.theses.fr/2016ECDM0004/document.
Повний текст джерелаBandit problems constitute a sequential dynamic allocation problem. The pulling agent has to explore its environment (i.e. the arms) to gather information on the one hand, and it has to exploit the collected clues to increase its rewards on the other hand. How to adequately balance the exploration phase and the exploitation phase is the crux of bandit problems and most of the efforts devoted by the research community from this fields has focused on finding the right exploitation/exploration tradeoff. In this dissertation, we focus on investigating two specific bandit problems: the contextual bandit problems and the multi-objective bandit problems. This dissertation provides two contributions. The first contribution is about the classification under partial supervision, which we encode as a contextual bandit problem with side informa- tion. This kind of problem is heavily studied by researchers working on social networks and recommendation systems. We provide a series of algorithms to solve the Bandit feedback problem that pertain to the Passive-Aggressive family of algorithms. We take advantage of its grounded foundations and we are able to show that our algorithms are much simpler to implement than state-of-the-art algorithms for bandit with partial feedback, and they yet achieve better perfor- mances of classification. For multi-objective multi-armed bandit problem (MOMAB), we propose an effective and theoretically motivated method to identify the Pareto front of arms. We in particular show that we can find all elements of the Pareto front with a minimal budget
Cvetkovic, Dragan. "Evolutionary multi-objective decision support systems for conceptual design." Thesis, University of Plymouth, 2000. http://hdl.handle.net/10026.1/2328.
Повний текст джерелаHartley, A. C. "The theory of parity non-conservation in atoms." Thesis, University of Oxford, 1989. https://ora.ox.ac.uk/objects/uuid:24d852a0-0f6f-4fea-8b41-db6a0b02b7c4.
Повний текст джерелаCaesium | 6s1⁄2 â 7s1⁄2 | 0.895 | (1±0.03) à 10-11 (-iea0QW/N) |
Thallium | 6p1⁄2 â 7p1⁄2 | -7.85 | (1±0.05) à 10-11 (-iea0QW/N) |
Thallium | 6p1⁄2 â 6p3⁄2 | -28.4 | (1±0.07) à 10-11 (-iea0QW/N) |
These are in very good agreement with the most extensive Many-Body Perturbation Theory calculations performed. Using our value for the caesium transition matrix element and the latest experimental results gives a value of QW = ~ 71.8 ± 1.8 ± 2.1 where the first error is experimental and the second is theoretical. This corresponds to a value of the standard model sin2ÎW = 0.230 ± 0.009 which is to be compared with the current world average value of 0.230 ± 0.005. We investigate the single particle EOM terms that were not included in the above calculation and find that they are concerned with the Exclusion Principle violating terms that are implicitly included in an RPA calculation. Other terms represent the valence contribution to certain two particle effects. Since the main two particle terms have not been included however, these correction terms do not lead to a significant increase in the accuracy of the calculation.
Jamain, Florian. "Représentations discrètes de l'ensemble des points non dominés pour des problèmes d'optimisation multi-objectifs." Phd thesis, Université Paris Dauphine - Paris IX, 2014. http://tel.archives-ouvertes.fr/tel-01070041.
Повний текст джерелаOujebbour, Fatima Zahra. "Méthodes et applications industrielles en optimisation multi-critère de paramètres de processus et de forme en emboutissage." Phd thesis, Université Nice Sophia Antipolis, 2014. http://tel.archives-ouvertes.fr/tel-00976639.
Повний текст джерелаCáceres, Sepúlveda Geraldine. "Relevance of Multi-Objective Optimization in the Chemical Engineering Field." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39783.
Повний текст джерелаAmouzgar, Kaveh. "Multi-objective optimization using Genetic Algorithms." Thesis, Högskolan i Jönköping, Tekniska Högskolan, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-19851.
Повний текст джерелаAmouzgar, Kaveh. "Metamodel based multi-objective optimization." Licentiate thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH. Forskningsmiljö Produktutveckling - Simulering och optimering, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-28432.
Повний текст джерелаGötz, Sebastian, Thomas Kühn, Christian Piechnick, Georg Püschel, and Uwe Aßmann. "A Models@run.time Approach for Multi-objective Self-optimizing Software." Springer, 2014. https://tud.qucosa.de/id/qucosa%3A75372.
Повний текст джерелаBahri, Oumayma. "A fuzzy framework for multi-objective optimization under uncertainty." Thesis, Lille 1, 2017. http://www.theses.fr/2017LIL10030/document.
Повний текст джерелаThis thesis is devoted to the study of multi-objective combinatorial optimization under uncertainty. In particular, we address multi-objective problems with fuzzy data, in which fuzziness is expressed by fuzzy triangular numbers. To handle such problems, our main idea is to extend the classical multi-objective concepts to fuzzy context. To handle such problems, we proposed a new Pareto approach between fuzzy-valued objectives (i.e. vectors of triangular fuzzy numbers). Then, an extension of Pareto-based metaheuristics is suggested as resolution methods. The proposed approach is thereafter illustrated on a bi-objective vehicle routing problem with fuzzy demands. At the second stage, we address robustness aspect in the multi-objective fuzzy context by proposing a new methodology of robustness evaluation of solutions. Finally, the experimental results on fuzzy benchmarks of vehicle routing problem prove the effectiveness and reliability of our approach
Lemesre, Julien. "Méthodes exactes pour l'optimisation combinatoire multi-objectif : conception et application." Lille 1, 2006. https://pepite-depot.univ-lille.fr/RESTREINT/Th_Num/2006/50376_2006_278.pdf.
Повний текст джерелаYoshikawa, Tomohiro, Daisuke Yamashiro, and Takeshi Furuhashi. "A Proposal of Visualization of Multi-Objective Pareto Solutions -Development of Mining Technique for Solutions-." IEEE, 2007. http://hdl.handle.net/2237/9482.
Повний текст джерелаIreland, David John. "Dielectric Antennas and Their Realisation Using a Pareto Dominance Multi-Objective Particle Swarm Optimisation Algorithm." Thesis, Griffith University, 2010. http://hdl.handle.net/10072/365312.
Повний текст джерелаThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Griffith School of Engineering
Science, Environment, Engineering and Technology
Full Text
Champion, Heather. "Beam angle and fluence map optimization for PARETO multi-objective intensity modulated radiation therapy treatment planning." Medical Physics, 2011. http://hdl.handle.net/1993/8910.
Повний текст джерелаVandervoort, Allan. "New Multi-Objective Optimization Techniques and Their Application to Complex Chemical Engineering Problems." Thesis, Université d'Ottawa / University of Ottawa, 2011. http://hdl.handle.net/10393/19785.
Повний текст джерелаGood, Nathan Andrew. "Multi-Objective Design Optimization Considering Uncertainty in a Multi-Disciplinary Ship Synthesis Model." Thesis, Virginia Tech, 2006. http://hdl.handle.net/10919/34532.
Повний текст джерелаMaster of Science
Hou, Ruizhe. "Optimal Latin Hypercube Designs for Computer Experiments Based on Multiple Objectives." Scholar Commons, 2018. http://scholarcommons.usf.edu/etd/7169.
Повний текст джерелаKamali, Aslan. "Developing a Decision Making Approach for District Cooling Systems Design using Multi-objective Optimization." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-208228.
Повний текст джерелаDie Energieverbrauchsraten haben in den letzten Jahrzehnten auf globaler Ebene dramatisch zugenommen. Diese Erhöhung ist zu einem großen Teil in den jüngst hohen Temperaturniveaus, vor allem in der Sommerzeit, begründet, die einen starken Anstieg der Nachfrage nach Klimaanlagen verursachen. Solche Ereignisse sind deutlich in Entwicklungsländern zu beobachten, vor allem in heißen Klimaregionen, wo Menschen vor allem konventionelle Klimaanlagensysteme benutzen. Diese Systeme verfügen meist über eine ineffiziente Leistungsfähigkeit und wirken sich somit negativ auf die Umwelt aus, was wiederum zur globalen Erwärmung beiträgt. In den letzten Jahren ist die Nachfrage nach Stadt- oder Fernkältetechnologien und -Netzwerken als Alternative zu konventionellen Systemen aufgrund ihrer höheren Effizienz und besseren ökologischen Verträglichkeit satrk gestiegen. Ein effizientes Design für Fernkühlsysteme zu erhalten, ist allerdings eine komplexe Aufgabe, die die Integration einer breite Palette von Kühltechnologien, verschiedener Konfigurationsmöglichkeiten von Netzwerk-Layouts und unterschiedlicher Energiequellen erfordert. Hierfür ist das Treffen kritischer Entscheidungen hinsichtlich einer Vielzahl von Möglichkeiten, Optionen und Technologien unabdingbar. Das Hauptziel dieser Arbeit ist es, ein Werkzeug zu entwickeln, das vorläufige Design-Konfigurationen und Betriebsmuster für Fernkälteenergiesysteme liefert, indem aureichend detaillierte Optimierungen durchgeführt werden. Zudem soll auch ein Ansatz zur Entscheidungsfindung vorgestellt werden, der Entscheidungsträger in einem frühen Planungsstadium bei der Bewertung städtischer Kühlungssysteme hinsichtlich der wirtschaftlichen Aspekte und Umweltleistung unterstützen soll. Unterschiedliche Aspekte dieser Problemstellung wurden in der Literatur von verschiedenen Forschern untersucht. Eine kurze Analyse des derzeitigen Stands der Technik ergab, dass mathematische Programmiermodelle die am weitesten verbreitete und erfolgreichste Methode für die Konfiguration und Gestaltung von Kühlsystemen für städtische Gebiete sind. Ein weiteres Ergebnis der Analyse war die Festlegung von Mehrzieloptimierungs-Modelles für die Unterstützung des Entscheidungsprozesses. Darauf basierend wurde im Rahmen der vorliegenden Arbeit ein Mehrzieloptimierungs-Modell für die Lösung des komplexen Entscheidungsfindungsprozesses bei der Gestaltung eines Kühlsystems für ein Stadtgebiet oder einen Bezirk entwickelt. Das Modell zielt darauf ab, mehrere Elemente des Kühlsystems zu optimieren, wie beispielsweise Kühlnetzwerke, Kühltechnologien sowie Kapazität und Lage der Systemtechnik. Zusätzlich werden verschiedene Energiequellen, auch solare wie Solarkonzentratoren, Vakuum-Solarkollektoren und PV-Module, berücksichtigt. Das Modell wurde auf Basis der gemischt-ganzzahlig linearen Optimierung (MILP) entwickelt und in GAMS Sprache implementiert. Zwei Fallstudien wurden mit dem entwickelten Modell untersucht. Die erste Fallstudie besteht aus sieben Gebäuden, die ein Wohnviertel darstellen, während die zweite Fallstudie einen Universitätscampus dominiert von Nichtwohngebäuden repräsentiert. Die Untersuchung wurde für mehrere Gruppen von Szenarien durchgeführt, wobei bestimmte Designparameter und Betriebsbedingungen überprüft werden, wie zum Beispiel die zur Verfügung stehende Fläche, Lage der Kühlanlage, örtliche Restriktionen der Kältespeicherung, Rohrpreise, Investitionskosten, konstante und variable Stromtarife, Strategie zur Einbindung der Solarenergie, Verfügbarkeit von Abwärme, Strategien der Lastenverschiebung, und die Wirkung der Außentemperatur in heißen Regionen auf die Leistung des Kühlsystems. Die Untersuchung bestand aus drei Stufen, wobei die jährlichen Gesamtkosten und die CO2-Emissionen die erste und zweite Einzelzieloptimierungsstufe darstellen. Die dritte Stufe war ein Pareto-Optimierung, die die beiden ersten Ziele kombiniert. Im Anschluss wurden nicht-dominante Lösungen, also Pareto-Lösungen, erzeugt, indem mehrere Pareto-Optimierungs-Szenarien basierend auf den Präferenzen der Entscheidungsträger abgebildet wurden. Schließlich wurde ein Ansatz zur Entscheidungsfindung entwickelt, um Entscheidungsträger bei der Auswahl einer bestimmten Lösung zu unterstützen, die am besten den Präferenzen des Planers oder des Entscheidungsträgers enstpricht, basierend auf der Differenz der Utopia und Nadir Werte, d.h. der jährlichen Gesamtkosten und CO2-Emissionen, die Ergebnis der einzelnen Optimierungsstufen sind
Adam, Zaeinulabddin Mohamed Ahmed. "Development and Applications of Multi-Objectives Signal Control Strategy during Oversaturated Conditions." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/28739.
Повний текст джерелаPh. D.
Ujihara, Rintaro. "Multi-objective optimization for model selection in music classification." Thesis, KTH, Optimeringslära och systemteori, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-298370.
Повний текст джерелаI och med genombrottet av maskininlärningstekniker har forskning kring känsloklassificering i musik sett betydande framsteg genom att kombinera olikamusikanalysverktyg med nya maskinlärningsmodeller. Trots detta är hur man förbehandlar ljuddatat och valet av vilken maskinklassificeringsalgoritm som ska tillämpas beroende på vilken typ av data man arbetar med samt målet med projektet. Denna uppsats samarbetspartner, Ichigoichie AB, utvecklar för närvarande ett system för att kategorisera musikdata enligt positiva och negativa känslor. För att höja systemets noggrannhet är målet med denna uppsats att experimentellt hitta bästa modellen baserat på sex musik-egenskaper (Mel-spektrogram, MFCC, HPSS, Onset, CENS samt Tonnetz) och ett antal olika maskininlärningsmodeller, inklusive Deep Learning-modeller. Varje modell hyperparameteroptimeras och utvärderas enligt paretooptimalitet med hänsyn till noggrannhet och beräkningstid. Resultaten visar att den mest lovande modellen uppnådde 95% korrekt klassificering med en beräkningstid på mindre än 15 sekunder.
Hopkins, Scott Dale. "Modeling and Multi-Objective Optimization of the Helsinki District Heating System and Establishing the Basis for Modeling the Finnish Power Network." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/23096.
Повний текст джерелаMaster of Science
Ordaz, Irian. "A probabilistic and multi-objective conceptual design methodology for the evaluation of thermal management systems on air-breathing hypersonic vehicles." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26478.
Повний текст джерелаCommittee Chair: Mavris, Dimitri N.; Committee Member: German, Brian J.; Committee Member: Osburg, Jan; Committee Member: Ruffin, Stephen M.; Committee Member: Schrage, Daniel P.. Part of the SMARTech Electronic Thesis and Dissertation Collection.
Nikolaou, Christos. "A multi-objective genetic algorithm optimisation using variable speed pumps in water distribution systems." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/6819/.
Повний текст джерелаBinois, Mickaël. "Uncertainty quantification on pareto fronts and high-dimensional strategies in bayesian optimization, with applications in multi-objective automotive design." Thesis, Saint-Etienne, EMSE, 2015. http://www.theses.fr/2015EMSE0805/document.
Повний текст джерелаThis dissertation deals with optimizing expensive or time-consuming black-box functionsto obtain the set of all optimal compromise solutions, i.e. the Pareto front. In automotivedesign, the evaluation budget is severely limited by numerical simulation times of the considered physical phenomena. In this context, it is common to resort to “metamodels” (models of models) of the numerical simulators, especially using Gaussian processes. They enable adding sequentially new observations while balancing local search and exploration. Complementing existing multi-objective Expected Improvement criteria, we propose to estimate the position of the whole Pareto front along with a quantification of the associated uncertainty, from conditional simulations of Gaussian processes. A second contribution addresses this problem from a different angle, using copulas to model the multi-variate cumulative distribution function. To cope with a possibly high number of variables, we adopt the REMBO algorithm. From a randomly selected direction, defined by a matrix, it allows a fast optimization when only a few number of variables are actually influential, but unknown. Several improvements are proposed, such as a dedicated covariance kernel, a selection procedure for the low dimensional domain and of the random directions, as well as an extension to the multi-objective setup. Finally, an industrial application in car crash-worthiness demonstrates significant benefits in terms of performance and number of simulations required. It has also been used to test the R package GPareto developed during this thesis
Daskilewicz, Matthew John. "Methods for parameterizing and exploring Pareto frontiers using barycentric coordinates." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47658.
Повний текст джерелаDeng, Qichen. "Antenna Optimization in Long-Term Evolution Networks." Thesis, KTH, Optimeringslära och systemteori, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-119147.
Повний текст джерелаNAIK, AMIT R. "TRADEOFF ANALYSIS FOR HELICAL GEAR REDUCTION UNITS." University of Cincinnati / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1129591522.
Повний текст джерелаLe, Trung-Dung. "Gestion de masses de données dans une fédération de nuages informatiques." Thesis, Rennes 1, 2019. http://www.theses.fr/2019REN1S101.
Повний текст джерелаCloud federations can be seen as major progress in cloud computing, in particular in the medical domain. Indeed, sharing medical data would improve healthcare. Federating resources makes it possible to access any information even on a mobile person with distributed hospital data on several sites. Besides, it enables us to consider larger volumes of data on more patients and thus provide finer statistics. Medical data usually conform to the Digital Imaging and Communications in Medicine (DICOM) standard. DICOM files can be stored on different platforms, such as Amazon, Microsoft, Google Cloud, etc. The management of the files, including sharing and processing, on such platforms, follows the pay-as-you-go model, according to distinct pricing models and relying on various systems (Relational Data Management Systems or DBMSs or NoSQL systems). In addition, DICOM data can be structured following traditional (row or column) or hybrid (row-column) data storages. As a consequence, medical data management in cloud federations raises Multi-Objective Optimization Problems (MOOPs) for (1) query processing and (2) data storage, according to users preferences, related to various measures, such as response time, monetary cost, qualities, etc. These problems are complex to address because of heterogeneous database engines, the variability (due to virtualization, large-scale communications, etc.) and high computational complexity of a cloud federation. To solve these problems, we propose a MedIcal system on clouD federAtionS (MIDAS). First, MIDAS extends IReS, an open source platform for complex analytics workflows executed over multi-engine environments, to solve MOOP in the heterogeneous database engines. Second, we propose an algorithm for estimating of cost values in a cloud environment, called Dynamic REgression AlgorithM (DREAM). This approach adapts the variability of cloud environment by changing the size of data for training and testing process to avoid using the expire information of systems. Third, Non-dominated Sorting Genetic Algorithm based ob Grid partitioning (NSGA-G) is proposed to solve the problem of MOOP is that the candidate space is large. NSGA-G aims to find an approximate optimal solution, while improving the quality of the optimal Pareto set of MOOP. In addition to query processing, we propose to use NSGA-G to find an approximate optimal solution for DICOM data configuration. We provide experimental evaluations to validate DREAM, NSGA-G with various test problem and dataset. DREAM is compared with other machine learning algorithms in providing accurate estimated costs. The quality of NSGA-G is compared to other NSGAs with many problems in MOEA framework. The DICOM dataset is also experimented with NSGA-G to find optimal solutions. Experimental results show the good qualities of our solutions in estimating and optimizing Multi-Objective Problem in a cloud federation
Faccioli, Rodrigo Antonio. "Algoritmo híbrido multi-objetivo para predição de estrutura terciária de proteínas." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/18/18153/tde-15052007-153736/.
Повний текст джерелаSeveral multi-objective optimization problems utilize evolutionary algorithms to find the best solution. Some of these algoritms make use of the Pareto front as a strategy to find these solutions. However, according to the literature, the Pareto front limitation for problems with up to three objectives can make its employment unsatisfactory in problems with four or more objectives. Moreover, many authors, in most cases, propose to remove the evolutionay algorithms because of Pareto front limitation. Nevertheless, characteristics of evolutionay algorithms qualify them to be employed in optimization problems, as it has being spread out by literature, preventing to eliminate it because the Pareto front elimination. Thus being, this work investigated to remove the Pareto front and for this utilized the Fuzzy logic, remaining itself thus the employ of evolutionary algorithms. The choice problem to investigate this remove was the protein tertiary structure prediction, because it is a open problem and extremely relevance to bioinformatic area.
Bakhsh, Ahmed. "A Posteriori and Interactive Approaches for Decision-Making with Multiple Stochastic Objectives." Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5897.
Повний текст джерелаPh.D.
Doctorate
Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering
Constantinou, Demetrakis. "Ant colony optimisation algorithms for solving multi-objective power-aware metrics for mobile ad hoc networks." Thesis, University of Pretoria, 2010. http://hdl.handle.net/2263/25981.
Повний текст джерела- Ant colony, multi-objective optimisation algorithms are suitable for mobile ad hoc networks. These algorithms allow for high adaptation to frequent changes in the topology of the network.
- All five algorithms yielded substantially better results than the non-dominated sorting genetic algorithm (NSGA-II) in terms of the quality of the solution.
- All the results prove that the EEMACOMP outperforms the other four ACO algorithms as well as the NSGA-II algorithm in terms of the number of solutions, closeness to the true Pareto front and diversity.
Thesis (PhD)--University of Pretoria, 2010.
Computer Science
unrestricted
Wilding, Paul Richard. "The Development of a Multi-Objective Optimization and Preference Tool to Improve the Design Process of Nuclear Power Plant Systems." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/7515.
Повний текст джерелаSthapit, Saurav. "Computation offloading for algorithms in absence of the Cloud." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31440.
Повний текст джерелаEssien, Mmekutmfon Sunday. "A multiobjective optimization model for optimal placement of solar collectors." Diss., University of Pretoria, 2012. http://hdl.handle.net/2263/30954.
Повний текст джерелаDissertation (MEng)--University of Pretoria, 2012.
Electrical, Electronic and Computer Engineering
MEng
Unrestricted
Pal, Anibrata. "Multi-objective optimization in learn to pre-compute evidence fusion to obtain high quality compressed web search indexes." Universidade Federal do Amazonas, 2016. http://tede.ufam.edu.br/handle/tede/5128.
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CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
The world of information retrieval revolves around web search engines. Text search engines are one of the most important source for routing information. The web search engines index huge volumes of data and handles billions of documents. The learn to rank methods have been adopted in the recent past to generate high quality answers for the search engines. The ultimate goal of these systems are to provide high quality results and, at the same time, reduce the computational time for query processing. Drawing direct correlation from the aforementioned fact; reading from smaller or compact indexes always accelerate data read or in other words, reduce computational time during query processing. In this thesis we study about using learning to rank method to not only produce high quality ranking of search results, but also to optimize another important aspect of search systems, the compression achieved in their indexes. We show that it is possible to achieve impressive gains in search engine index compression with virtually no loss in the final quality of results by using simple, yet effective, multi objective optimization techniques in the learning process. We also used basic pruning techniques to find out the impact of pruning in the compression of indexes. In our best approach, we were able to achieve more than 40% compression of the existing index, while keeping the quality of results at par with methods that disregard compression.
Máquinas de busca web para a web indexam grandes volumes de dados, lidando com coleções que muitas vezes são compostas por dezenas de bilhões de documentos. Métodos aprendizagem de máquina têm sido adotados para gerar as respostas de alta qualidade nesses sistemas e, mais recentemente, há métodos de aprendizagem de máquina propostos para a fusão de evidências durante o processo de indexação das bases de dados. Estes métodos servem então não somente para melhorar a qualidade de respostas em sistemas de busca, mas também para reduzir custos de processamento de consultas. O único método de fusão de evidências em tempo de indexação proposto na literatura tem como foco exclusivamente o aprendizado de funções de fusão de evidências que gerem bons resultados durante o processamento de consulta, buscando otimizar este único objetivo no processo de aprendizagem. O presente trabalho apresenta uma proposta onde utiliza-se o método de aprendizagem com múltiplos objetivos, visando otimizar, ao mesmo tempo, tanto a qualidade de respostas produzidas quando o grau de compressão do índice produzido pela fusão de rankings. Os resultados apresentados indicam que a adoção de um processo de aprendizagem com múltiplos objetivos permite que se obtenha melhora significativa na compressão dos índices produzidos sem que haja perda significativa na qualidade final do ranking produzido pelo sistema.
Furuhashi, Takeshi, Tomohiro Yoshikawa, and Fumiya Kudo. "A Study on Analysis of Design Variables in Pareto Solutions for Conceptual Design Optimization Problem of Hybrid Rocket Engine." IEEE, 2011. http://hdl.handle.net/2237/20699.
Повний текст джерелаVanden, Boom Michael T. "Weak cost automata over infinite trees." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:16c6de98-545f-4d2d-acda-efc040049452.
Повний текст джерелаBobrow, Kirsten Louise. "The effects of childbearing on women's body mass index, and on the risk of diabetes mellitus, or ischaemic heart disease after the menopause." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:5c86d91f-973d-4ff7-a8e7-4e8642a541df.
Повний текст джерелаPatel, Chirag B. "A multi-objective stochastic approach to combinatorial technology space exploration." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29647.
Повний текст джерелаCommittee Chair: Dr. Dimitri N. Mavris; Committee Member: Dr. Brian J. German; Committee Member: Dr. Daniel P. Schrage; Committee Member: Dr. Frederic Villeneuve; Committee Member: Dr. Michelle R. Kirby; Committee Member: Ms. Antje Lembcke. Part of the SMARTech Electronic Thesis and Dissertation Collection.
Pilati, Francesco. "Multi-objective Models and Methods for Design and Management of Sustainable Logistic Systems." Doctoral thesis, Università degli studi di Padova, 2016. http://hdl.handle.net/11577/3424337.
Повний текст джерелаLa logistica viene tipicamente definita come l’insieme di quelle attività di progettazione e gestione di sistemi fisici ed informativi necessari per consentire alle diverse tipologie di merci di superare lo spazio ed il tempo. I modelli ed i metodi tradizionali per la progettazione e gestione dei sistemi logistici si focalizzano sull’ottimizzazione delle prestazioni tecnico-economiche. Tuttavia, le attività logistiche si contraddistinguono per un elevato impatto ambientale. Solo per citare un esempio, il consumo di energia per il trasporto merci ha raggiunto negli ultimi anni il 13% dell’energia complessivamente utilizzata su scala mondiale, pari cioè a 40 EJ annui. Gli approcci innovativi per la progettazione e gestione di sistemi logistici devono necessariamente garantire la loro sostenibilità non solo da un punto di vista tecnico ed economico, ma anche da quello ambientale. A tal fine, l’ottimizzazione multi-obiettivo è di notevole aiuto. Questo metodo di programmazione matematica permette di ottimizzare sistematicamente e simultaneamente un insieme di funzioni obiettivo spesso contrastanti tra loro. Alla luce di questo scenario, lo scopo di questa tesi di dottorato è quello di sviluppare, proporre e validare modelli e metodi multi-obiettivo innovativi per la progettazione e la gestione di sistemi logistici sostenibili ottimizzando contemporaneamente le loro prestazioni tecniche, economiche ed ambientali. I modelli sviluppati permettono di gestire nella sua interezza il flusso di materiali dai fornitori ai reparti di fabbricazione o assemblaggio e da questi ai clienti finali attraverso le necessarie attività di distribuzione, stoccaggio e prelievo all’interno e tra gli attori della catena logistica. E’ stato sviluppato un sistema per il supporto decisionale atto a minimizzare contemporaneamente il costo operativo, la carbon footprint ed il tempo di trasporto di reti distributive multi-livello e multi-modali prendendo in considerazione le più importanti caratteristiche dei prodotti trasportati. Per quanto riguarda i sistemi di immagazzinamento e stoccaggio, questa tesi affronta sia le tematiche di progettazione sia quelle operative. Un modello di ottimizzazione multi-obiettivo è proposto per definire la configurazione degli edifici atti allo stoccaggio merci, ovvero la loro lunghezza, larghezza ed altezza, al fine di minimizzare il tempo di prelievo, il costo totale e la carbon footprint. Queste ultime due funzioni obiettivo sono state valutate considerando l’intero ciclo di vita del magazzino. Tutte le attività relative alle fasi di installazione ed esercizio dell’edificio vengono contabilizzate sia da un punto di vista economico che ambientale. Per quanto concerne la gestione operativa di un sistema di immagazzinamento, questa tesi affrontata il problema dell’assegnazione dei prodotti ai vani di stoccaggio. Si è definito un modello di ottimizzazione multi-obiettivo per minimizzare contestualmente il tempo e l’energia necessari alle attività di prelievo e stoccaggio. Per modellare opportunamente le funzioni obiettivo temporali ed energetiche sono stati valutati accuratamente sia i profili di moto dei veicoli per lo stoccaggio merce sia le caratteristiche dei prodotti da immagazzinare. Per concludere, i modelli ed i metodi presentati sono stati validati e testati con casi studio provenienti dall’industria alimentare. I risultati ottenuti dimostrano come sia possibile ridurre drasticamente l’impatto ambientale di questi sistemi logistici a scapito di un trascurabile peggioramento delle prestazioni tecnico ed economiche.
DESHMUKH, DINAR VIVEK. "Design Optimization of Mechanical Components." University of Cincinnati / OhioLINK, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1028738547.
Повний текст джерелаJaini, Nor. "An efficient ranking analysis in multi-criteria decision making." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/an-efficient-ranking-analysis-in-multicriteria-decision-making(c5a694d5-fd43-434f-9f9f-b86f7581b97c).html.
Повний текст джерелаLu, Ming. "Synergetic Attenuation of Stray Magnetic Field in Inductive Power Transfer." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/78621.
Повний текст джерелаPh. D.