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Rozprawy doktorskie na temat „Optimization algorithms”

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Data publikacji: 4 czerwca 2021
Data aktualizacji: 25 lipca 2025

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1

Astete, morales Sandra. "Contributions to Convergence Analysis of Noisy Optimization Algorithms." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS327/document.

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Cette thèse montre des contributions à l'analyse d'algorithmes pour l'optimisation de fonctions bruitées. Les taux de convergences (regret simple et regret cumulatif) sont analysés pour les algorithmes de recherche linéaire ainsi que pour les algorithmes de recherche aléatoires. Nous prouvons que les algorithmes basé sur la matrice hessienne peuvent atteindre le même résultat que certaines algorithmes optimaux, lorsque les paramètres sont bien choisis. De plus, nous analysons l'ordre de convergence des stratégies évolutionnistes pour des fonctions bruitées. Nous déduisons une convergence log-l
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Reimann, Axel. "Evolutionary algorithms and optimization." Doctoral thesis, [S.l. : s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=969093497.

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Parpas, Panayiotis. "Algorithms for stochastic optimization." Thesis, Imperial College London, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.434980.

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Johnson, Jared. "Algorithms for Rendering Optimization." Doctoral diss., University of Central Florida, 2012. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5329.

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This dissertation explores algorithms for rendering optimization realizable within a modern, complex rendering engine. The first part contains optimized rendering algorithms for ray tracing. Ray tracing algorithms typically provide properties of simplicity and robustness that are highly desirable in computer graphics. We offer several novel contributions to the problem of interactive ray tracing of complex lighting environments. We focus on the problem of maintaining interactivity as both geometric and lighting complexity grows without effecting the simplicity or robustness of ray tracing. Fir
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CESARI, TOMMASO RENATO. "ALGORITHMS, LEARNING, AND OPTIMIZATION." Doctoral thesis, Università degli Studi di Milano, 2020. http://hdl.handle.net/2434/699354.

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This thesis covers some algorithmic aspects of online machine learning and optimization. In Chapter 1 we design algorithms with state-of-the-art regret guarantees for the problem dynamic pricing. In Chapter 2 we move on to an asynchronous online learning setting in which only some of the agents in the network are active at each time step. We show that when information is shared among neighbors, knowledge about the graph structure might have a significantly different impact on learning rates depending on how agents are activated. In Chapter 3 we investigate the online problem of multivariate no
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Stults, Ian Collier. "A multi-fidelity analysis selection method using a constrained discrete optimization formulation." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31706.

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Thesis (Ph.D)--Aerospace Engineering, Georgia Institute of Technology, 2010.<br>Committee Chair: Mavris, Dimitri; Committee Member: Beeson, Don; Committee Member: Duncan, Scott; Committee Member: German, Brian; Committee Member: Kumar, Viren. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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7

Rafique, Abid. "Communication optimization in iterative numerical algorithms : an algorithm-architecture interaction." Thesis, Imperial College London, 2014. http://hdl.handle.net/10044/1/17837.

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Trading communication with redundant computation can increase the silicon efficiency of common hardware accelerators like FPGA and GPU in accelerating sparse iterative numerical algorithms. While iterative numerical algorithms are extensively used in solving large-scale sparse linear system of equations and eigenvalue problems, they are challenging to accelerate as they spend most of their time in communication-bound operations, like sparse matrix-vector multiply (SpMV) and vector-vector operations. Communication is used in a general sense to mean moving the matrix and the vectors within the c
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Dost, Banu. "Optimization algorithms for biological data." Diss., [La Jolla] : University of California, San Diego, 2010. http://wwwlib.umi.com/cr/ucsd/fullcit?p3397170.

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Thesis (Ph. D.)--University of California, San Diego, 2010.<br>Title from first page of PDF file (viewed March 23, 2010). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 149-159).
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9

Xiong, Xiaoping. "Stochastic optimization algorithms and convergence /." College Park, Md. : University of Maryland, 2005. http://hdl.handle.net/1903/2360.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2005.<br>Thesis research directed by: Business and Management. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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10

Quttineh, Nils-Hassan. "Algorithms for Costly Global Optimization." Licentiate thesis, Mälardalen University, School of Education, Culture and Communication, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-5970.

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<p>There exists many applications with so-called costly problems, which means that the objective function you want to maximize or minimize cannot be described using standard functions and expressions. Instead one considers these objective functions as ``black box'' where the parameter values are sent in and a function value is returned. This implies in particular that no derivative information is available.The reason for describing these problems as expensive is that it may take a long time to calculate a single function value. The black box could, for example, solve a large system of differen
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11

Zhou, Yi. "Optimization Algorithms for Clique Problems." Thesis, Angers, 2017. http://www.theses.fr/2017ANGE0013/document.

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Cette thèse présente des algorithmes de résolution de quatre problèmes de clique : clique de poids maximum (MVWCP), s-plex maximum (MsPlex), clique maximum équilibrée dans un graphe biparti (MBBP) et clique partition (CPP). Les trois premiers problèmes sont des généralisations ou relaxations du problème de la clique maximum, tandis que le dernier est un problème de couverture. Ces problèmes, ayant de nombreuses applications pratiques, sont NP-difficiles, rendant leur résolution ardue dans le cas général. Nous présentons ici des algorithmes de recherche locale, principalement basés sur la reche
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12

Liu, Qiuliang. "Image mosaic algorithms and optimization." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 58 p, 2007. http://proquest.umi.com/pqdweb?did=1400965051&sid=9&Fmt=2&clientId=8331&RQT=309&VName=PQD.

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13

李國誠 and Kwok-shing Lee. "Convergences of stochastic optimization algorithms." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B3025632X.

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14

Roberts, Christopher. "Genetic algorithms for cluster optimization." Thesis, University of Birmingham, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368792.

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15

Caramanis, Constantine (Constantine Michael) 1977. "Adaptable optimization : theory and algorithms." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/38301.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.<br>Includes bibliographical references (p. 189-200).<br>Optimization under uncertainty is a central ingredient for analyzing and designing systems with incomplete information. This thesis addresses uncertainty in optimization, in a dynamic framework where information is revealed sequentially, and future decisions are adaptable, i.e., they depend functionally on the information revealed in the past. Such problems arise in applications where actions are repeated over a time horizon
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16

Hu, Liujia. "Convergent algorithms in simulation optimization." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54883.

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It is frequently the case that deterministic optimization models could be made more practical by explicitly incorporating uncertainty. The resulting stochastic optimization problems are in general more difficult to solve than their deterministic counterparts, because the objective function cannot be evaluated exactly and/or because there is no explicit relation between the objective function and the corresponding decision variables. This thesis develops random search algorithms for solving optimization problems with continuous decision variables when the objective function values can be estima
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Collether, John. "Portfolio optimization by heuristic algorithms." Thesis, University of Essex, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.635985.

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Portfolio optimization is a major activity in business. It is intensively studied by researchers. Conventional portfolio optimization research made simplifying assumptions. For example, they assumed no constraint in how many assets one holds (cardinality constraint). They also assume no minimum and maximum holding sizes (holding size constraint). Once these assumptions are relaxed, conventional methods become inapplicable. New methods are demanded. Threshold Accepting is an established algorithm in the extended portfolio optimization problem.
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18

Arvidsson, Elisabeth. "Optimization algorithms for Quantum Annealing." Thesis, KTH, Fysik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279447.

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19

Viitanen, Sami. "Some new global optimization algorithms /." Åbo : Åbo Akad. Förl, 1997. http://www.gbv.de/dms/goettingen/239457927.pdf.

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20

Naji, Azimi Zahra <1982&gt. "Algorithms for Combinatorial Optimization Problems." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2010. http://amsdottorato.unibo.it/2695/1/Naji_Azimi_Zahra_Tesi.pdf.

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Naji, Azimi Zahra <1982&gt. "Algorithms for Combinatorial Optimization Problems." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2010. http://amsdottorato.unibo.it/2695/.

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Harris, Steven C. "A genetic algorithm for robust simulation optimization." Ohio : Ohio University, 1996. http://www.ohiolink.edu/etd/view.cgi?ohiou1178645751.

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23

Samek, Michal. "Optimization of Aircraft Tracker Parameters." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2015. http://www.nusl.cz/ntk/nusl-234937.

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Diplomová práce se zabývá optimalizací systému pro sledování letadel, využívaného pro řízení letového provozu. Je popsána metodika vyhodnocování přesnosti sledovacího systému a přehled relevantních algoritmů pro sledování objektů. Dále jsou navrženy tři přístupy k řešení problému. První se pokouší identifikovat parametry filtrovacích algoritmů pomocí algoritmu Expectation-Maximisation, implementací metody maximální věrohodnosti. Druhý přístup je založen na prostých odhadech parametrů normálního rozložení z naměřených a referenčních dat. Nakonec je zkoumána možnost řešení pomocí optimalizačního
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24

Aggarwal, Varun. "Analog circuit optimization using evolutionary algorithms and convex optimization." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/40525.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.<br>Includes bibliographical references (p. 83-88).<br>In this thesis, we analyze state-of-art techniques for analog circuit sizing and compare them on various metrics. We ascertain that a methodology which improves the accuracy of sizing without increasing the run time or the designer effort is a contribution. We argue that the accuracy of geometric programming can be improved without adversely influencing the run time or increasing the designer's effort. This is facilitated by dec
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25

Pelikan, Martin. "Hierarchical Bayesian optimization algorithm : toward a new generation of evolutionary algorithms /." Berlin [u.a.] : Springer, 2005. http://www.loc.gov/catdir/toc/fy053/2004116659.html.

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Corbineau, Marie-Caroline. "Proximal and interior point optimization strategies in image recovery." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLC085/document.

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Les problèmes inverses en traitement d'images peuvent être résolus en utilisant des méthodes variationnelles classiques, des approches basées sur l'apprentissage profond, ou encore des stratégies bayésiennes. Bien que différentes, ces approches nécessitent toutes des algorithmes d'optimisation efficaces. L'opérateur proximal est un outil important pour la minimisation de fonctions non lisses. Dans cette thèse, nous illustrons la polyvalence des algorithmes proximaux en les introduisant dans chacune des trois méthodes de résolution susmentionnées.Tout d'abord, nous considérons une formulation v
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Cruz, Mencía Francisco. "Enhancing performance on combinatorial optimization algorithms." Doctoral thesis, Universitat Autònoma de Barcelona, 2018. http://hdl.handle.net/10803/665199.

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L’optimització combinatòria és un tipus específic d’optimització matemàtica on el domini de les variables és discret. Aquest tipus de problemes d’optimització tenen una gran aplicabilitat degut a la seva capacitat d’optimització sobre objectes unitaris i no divisibles. Més enllà dels algoritmes genèrics, la comunitat investigadora és molt activa proposant algorismes capaços d’abordar problemes d’optimització combinatòria per a problemes específics. L’objectiu d’aquesta tesi és investigar com ampliar l’aplicabilitat d’algorismes d’optimització combinatoria que exploten l’estructura dels problem
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28

Ericsson, Kenneth, and Robert Grann. "Image optimization algorithms on an FPGA." Thesis, Mälardalen University, School of Innovation, Design and Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-5727.

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<p> </p><p>In this thesis a method to compensate camera distortion is developed for an FPGA platform as part of a complete vision system. Several methods and models is presented and described to give a good introduction to the complexity of the problems that is overcome with the developed method. The solution to the core problem is shown to have a good precision on a sub-pixel level.</p><p> </p>
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29

Amouzgar, 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.

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In this thesis, the basic principles and concepts of single and multi-objective Genetic Algorithms (GA) are reviewed. Two algorithms, one for single objective and the other for multi-objective problems, which are believed to be more efficient are described in details. The algorithms are coded with MATLAB and applied on several test functions. The results are compared with the existing solutions in literatures and shows promising results. Obtained pareto-fronts are exactly similar to the true pareto-fronts with a good spread of solution throughout the optimal region. Constraint handling techniq
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Tian, Zhong Huan. "Gender based meta-heuristic optimization algorithms." Thesis, University of Macau, 2017. http://umaclib3.umac.mo/record=b3691331.

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Weicker, Karsten. "Evolutionary algorithms and dynamic optimization problems /." Osnabrück : Der Andere Verl, 2003. http://www.gbv.de/dms/ilmenau/toc/365163716weick.PDF.

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Raj, Ashish. "Evolutionary Optimization Algorithms for Nonlinear Systems." DigitalCommons@USU, 2013. http://digitalcommons.usu.edu/etd/1520.

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Many real world problems in science and engineering can be treated as optimization problems with multiple objectives or criteria. The demand for fast and robust stochastic algorithms to cater to the optimization needs is very high. When the cost function for the problem is nonlinear and non-differentiable, direct search approaches are the methods of choice. Many such approaches use the greedy criterion, which is based on accepting the new parameter vector only if it reduces the value of the cost function. This could result in fast convergence, but also in misconvergence where it could lead the
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33

Carlson, Susan Elizabeth. "Component selection optimization using genetic algorithms." Diss., Georgia Institute of Technology, 1993. http://hdl.handle.net/1853/17886.

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Farah, Abdulkadir. "Differential evolution algorithms for network optimization." Thesis, University of Reading, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.602400.

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Many real world optimization problems are difficult to solve, therefore, when solving such problems it is wise to employ efficient optimization algorithms which are capable of handling the problem complexities and of finding optimal or near optimal solutions within a reasonable time and without using excessive computational resources. The objective of this research is to develop Differential Evolution (DE) algorithms with improved performance capable of solving difficult and challenging global constrained and unconstrained optimization problems, as well as extending the application of the thes
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35

Fathi, Bayda. "Gradient optimization algorithms with fast convergence." Thesis, Cardiff University, 2013. http://orca.cf.ac.uk/50398/.

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The most common class of methods for solving linear systems is the class of gradient algorithms, the most famous of which being the steepest descent (SD) algorithm. Linear systems equivalent to the quadratic optimization problems where the coefficient matrix of the linear system is the Hessian of the corresponding quadratic function. In recent years, the development of a particular gradient algorithm, namely the Barzilai-Borwein (BB) algorithm, has instigated a lot of research in the area of optimization and many algorithms now exist which have faster rates of convergence than those possessed
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Chen, Qin, and 陈琴. "Algorithms for some combinatorial optimization problems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B46589302.

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Mota, Joao F. C. "Communication-Efficient Algorithms For Distributed Optimization." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/283.

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This thesis is concerned with the design of distributed algorithms for solving optimization problems. The particular scenario we consider is a network with P compute nodes, where each node p has exclusive access to a cost function fp. We design algorithms in which all the nodes cooperate to find the minimum of the sum of all the cost functions, f1 + · · · + fP . Several problems in signal processing, control, and machine learning can be posed as such optimization problems. Given that communication is often the most energy-consuming operation in networks and, many times, also the slowest one, i
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ABOUSABEA, Emad Mohamed Abd Elrahman. "Optimization algorithms for video service delivery." Phd thesis, Institut National des Télécommunications, 2012. http://tel.archives-ouvertes.fr/tel-00762636.

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The aim of this thesis is to provide optimization algorithms for accessing video services either in unmanaged or managed ways. We study recent statistics about unmanaged video services like YouTube and propose suitable optimization techniques that could enhance files accessing and reduce their access costs. Moreover, this cost analysis plays an important role in decision making about video files caching and hosting periods on the servers. Under managed video services called IPTV, we conducted experiments for an open-IPTV collaborative architecture between different operators. This model is ana
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CARBONO, ALONSO JOAQUIN JUVINAO. "MOORING PATTERN OPTIMIZATION USING GENETIC ALGORITHMS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2005. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8242@1.

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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>GRUPO DE TECNOLOGIA DE COMPUTAÇÃO GRÁFICA - PUC-RIO<br>Com o crescimento da demanda de óleo, as empresas de petróleo têm sido forçadas a explorar novas reservas em águas cada vez mais profundas. Em função do alto custo das operações de exploração de petróleo, torna-se necessário o desenvolvimento de tecnologias capazes de aumentar a eficiência e reduzir os custos envolvidos. Neste contexto, a utilização de unidades flutuantes torna-se cada vez mais freqüente em águas profundas. O posicionamento das unidades flutuantes durant
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Tang, Wang-Rei 1975. "The optimization of data compression algorithms." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/81553.

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Chicoisne, Renaud Pierre. "Efficient algorithms for risk averse optimization." Tesis, Universidad de Chile, 2015. http://repositorio.uchile.cl/handle/2250/135193.

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Doctor en Sistemas de Ingeniería<br>Muchos problemas de decisión industriales o logísticos pueden ser vistos como problemas de optimización y para muchos de ellos no es razonable ocupar datos deterministas. Como veremos en este trabajo en el contexto de despachos de emergencia o de planificación de seguridad, las condiciones reales son desconocidas y tomar decisiones sin considerar esta incertidumbre pueden llevar a resultados catastróficos. La teoría y la aplicación de optimización bajo incertidumbre es un tema que ha generado un amplio área de investigación. Sin embargo, aún existen gra
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Lovestead, Raymond L. "Helical Antenna Optimization Using Genetic Algorithms." Thesis, Virginia Tech, 1999. http://hdl.handle.net/10919/35295.

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The genetic algorithm (GA) is used to design helical antennas that provide a significantly larger bandwidth than conventional helices with the same size. Over the bandwidth of operation, the GA-optimized helix offers considerably smaller axial-ratio and slightly higher gain than the conventional helix. Also, the input resistance remains relatively constant over the bandwidth. On the other hand, for nearly the same bandwidth and gain, the GA-optimized helix offers a size reduction of 2:1 relative to the conventional helix. The optimization is achieved by allowing the genetic algorithm to contro
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Shi, Yi. "Algorithms and Optimization for Wireless Networks." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/29480.

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Recently, many new types of wireless networks have emerged for both civil and military applications, such as wireless sensor networks, ad hoc networks, among others. To improve the performance of these wireless networks, many advanced communication techniques have been developed at the physical layer. For both theoretical and practical purposes, it is important for a network researcher to understand the performance limits of these new wireless networks. Such performance limits are important not only for theoretical understanding, but also in that they can be used as benchmarks for the design o
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Sun, Chuangchuang. "Rank-Constrained Optimization: Algorithms and Applications." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1531750343188114.

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Ren, Jintong. "Optimization algorithms for graph layout problems." Thesis, Angers, 2020. https://tel.archives-ouvertes.fr/tel-03178385.

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Cette thèse considère deux problèmes de disposition des graphes : le problème de la bande passante cyclique (CBP) et le problème de l’agencement linéaire minimum (MinLA). Le CBP est une extension naturelle du problème de minimisation de la bande passante (BMP) et le MinLA est un problème de somme minimale. Ces problèmes sont largement appliqués dans la vie réelle. Puisqu’ils sont NP-difficile, il est difficile de les résoudre dans le cas général. Par conséquent, cette thèse est consacrée au développement d’algorithmes heuristiques efficaces pour faire face à ces problèmes. Plus précisément, no
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46

Jedor, Matthieu. "Bandit algorithms for recommender system optimization." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASM027.

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Dans cette thèse de doctorat, nous étudions l'optimisation des systèmes de recommandation dans le but de fournir des suggestions de produits plus raffinées pour un utilisateur.La tâche est modélisée à l'aide du cadre des bandits multi-bras.Dans une première partie, nous abordons deux problèmes qui se posent fréquemment dans les systèmes de recommandation : le grand nombre d'éléments à traiter et la gestion des contenus sponsorisés.Dans une deuxième partie, nous étudions les performances empiriques des algorithmes de bandit et en particulier comment paramétrer les algorithmes traditionnels pour
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Kroyan, Julia. "Trust-search algorithms for unconstrained optimization /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2004. http://wwwlib.umi.com/cr/ucsd/fullcit?p3120456.

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Wike, Carl E. 1948. "Supply chain optimization : formulations and algorithms." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/9763.

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Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 1999.<br>Includes bibliographical references (leaves 103-106).<br>In this thesis, we develop practical solution methods for a supply chain optimization problem: a multi-echelon, un capacitated, time-expanded network of distribution cen­ters and stores, for which we seek the shipping schedule that minimizes total inventory, backlogging, and shipping costs, assuming deterministic, time-varying demand over a fixed time horizon for a single product. Because of fixed ordering and shipping c
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Themelis, Andreas. "Proximal algorithms for structured nonconvex optimization." Thesis, IMT Alti Studi Lucca, 2018. http://e-theses.imtlucca.it/262/1/Themelis_phdthesis.pdf.

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Due to their simplicity and versatility, splitting algorithms are often the methods of choice for many optimization problems arising in engineering. “Splitting” complex problems into simpler subtasks, their complexity scales well with problem size, making them particularly suitable for large-scale applications where other popular methods such as IP or SQP cannot be employed. There are, however, two major downsides: 1) there is no satisfactory theory in support of their employment for nonconvex problems, and 2) their efficacy is severely affected by ill conditioning. Many attempts have b
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Strappaveccia, Francesco <1982&gt. "Many-core Algorithms for Combinatorial Optimization." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/6949/1/Strappaveccia_Francesco_tesi.pdf.

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Combinatorial Optimization is becoming ever more crucial, in these days. From natural sciences to economics, passing through urban centers administration and personnel management, methodologies and algorithms with a strong theoretical background and a consolidated real-word effectiveness is more and more requested, in order to find, quickly, good solutions to complex strategical problems. Resource optimization is, nowadays, a fundamental ground for building the basements of successful projects. From the theoretical point of view, Combinatorial Optimization rests on stable and strong foundation
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