Dissertations / Theses on the topic 'Algorithems'
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Saadane, Sofiane. "Algorithmes stochastiques pour l'apprentissage, l'optimisation et l'approximation du régime stationnaire." Thesis, Toulouse 3, 2016. http://www.theses.fr/2016TOU30203/document.
Full textIn this thesis, we are studying severa! stochastic algorithms with different purposes and this is why we will start this manuscript by giving historicals results to define the framework of our work. Then, we will study a bandit algorithm due to the work of Narendra and Shapiro whose objectif was to determine among a choice of severa! sources which one is the most profitable without spending too much times on the wrong orres. Our goal is to understand the weakness of this algorithm in order to propose an optimal procedure for a quantity measuring the performance of a bandit algorithm, the regret. In our results, we will propose an algorithm called NS over-penalized which allows to obtain a minimax regret bound. A second work will be to understand the convergence in law of this process. The particularity of the algorith is that it converges in law toward a non-diffusive process which makes the study more intricate than the standard case. We will use coupling techniques to study this process and propose rates of convergence. The second work of this thesis falls in the scope of optimization of a function using a stochastic algorithm. We will study a stochastic version of the so-called heavy bali method with friction. The particularity of the algorithm is that its dynamics is based on the ali past of the trajectory. The procedure relies on a memory term which dictates the behavior of the procedure by the form it takes. In our framework, two types of memory will investigated : polynomial and exponential. We will start with general convergence results in the non-convex case. In the case of strongly convex functions, we will provide upper-bounds for the rate of convergence. Finally, a convergence in law result is given in the case of exponential memory. The third part is about the McKean-Vlasov equations which were first introduced by Anatoly Vlasov and first studied by Henry McKean in order to mode! the distribution function of plasma. Our objective is to propose a stochastic algorithm to approach the invariant distribution of the McKean Vlasov equation. Methods in the case of diffusion processes (and sorne more general pro cesses) are known but the particularity of McKean Vlasov process is that it is strongly non-linear. Thus, we will have to develop an alternative approach. We will introduce the notion of asymptotic pseudotrajectory in odrer to get an efficient procedure
Corbineau, Marie-Caroline. "Proximal and interior point optimization strategies in image recovery." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLC085/document.
Full textInverse problems in image processing can be solved by diverse techniques, such as classical variational methods, recent deep learning approaches, or Bayesian strategies. Although relying on different principles, these methods all require efficient optimization algorithms. The proximity operator appears as a crucial tool in many iterative solvers for nonsmooth optimization problems. In this thesis, we illustrate the versatility of proximal algorithms by incorporating them within each one of the aforementioned resolution methods.First, we consider a variational formulation including a set of constraints and a composite objective function. We present PIPA, a novel proximal interior point algorithm for solving the considered optimization problem. This algorithm includes variable metrics for acceleration purposes. We derive convergence guarantees for PIPA and show in numerical experiments that it compares favorably with state-of-the-art algorithms in two challenging image processing applications.In a second part, we investigate a neural network architecture called iRestNet, obtained by unfolding a proximal interior point algorithm over a fixed number of iterations. iRestNet requires the expression of the logarithmic barrier proximity operator and of its first derivatives, which we provide for three useful types of constraints. Then, we derive conditions under which this optimization-inspired architecture is robust to an input perturbation. We conduct several image deblurring experiments, in which iRestNet performs well with respect to a variational approach and to state-of-the-art deep learning methods.The last part of this thesis focuses on a stochastic sampling method for solving inverse problems in a Bayesian setting. We present an accelerated proximal unadjusted Langevin algorithm called PP-ULA. This scheme is incorporated into a hybrid Gibbs sampler used to perform joint deconvolution and segmentation of ultrasound images. PP-ULA employs the majorize-minimize principle to address non log-concave priors. As shown in numerical experiments, PP-ULA leads to a significant time reduction and to very satisfactory deconvolution and segmentation results on both simulated and real ultrasound data
Harris, Steven C. "A genetic algorithm for robust simulation optimization." Ohio : Ohio University, 1996. http://www.ohiolink.edu/etd/view.cgi?ohiou1178645751.
Full textAlkindy, Bassam. "Combining approaches for predicting genomic evolution." Thesis, Besançon, 2015. http://www.theses.fr/2015BESA2012/document.
Full textIn Bioinformatics, understanding how DNA molecules have evolved over time remains an open and complex problem.Algorithms have been proposed to solve this problem, but they are limited either to the evolution of a given character (forexample, a specific nucleotide), or conversely focus on large nuclear genomes (several billion base pairs ), the latter havingknown multiple recombination events - the problem is NP complete when you consider the set of all possible operationson these sequences, no solution exists at present. In this thesis, we tackle the problem of reconstruction of ancestral DNAsequences by focusing on the nucleotide chains of intermediate size, and have experienced relatively little recombinationover time: chloroplast genomes. We show that at this level the problem of the reconstruction of ancestors can be resolved,even when you consider the set of all complete chloroplast genomes currently available. We focus specifically on the orderand ancestral gene content, as well as the technical problems this raises reconstruction in the case of chloroplasts. Weshow how to obtain a prediction of the coding sequences of a quality such as to allow said reconstruction and how toobtain a phylogenetic tree in agreement with the largest number of genes, on which we can then support our back in time- the latter being finalized. These methods, combining the use of tools already available (the quality of which has beenassessed) in high performance computing, artificial intelligence and bio-statistics were applied to a collection of more than450 chloroplast genomes
Astete, morales Sandra. "Contributions to Convergence Analysis of Noisy Optimization Algorithms." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS327/document.
Full textThis thesis exposes contributions to the analysis of algorithms for noisy functions. It exposes convergence rates for linesearch algorithms as well as for random search algorithms. We prove in terms of Simple Regret and Cumulative Regret that a Hessian based algorithm can reach the same results as some optimal algorithms in the literature, when parameters are tuned correctly. On the other hand we analyse the convergence order of Evolution Strategies when solving noisy functions. We deduce log-log convergence. We also give a lower bound for the convergence rate of the Evolution Strategies. We extend the work on revaluation by applying it to a discrete settings. Finally we analyse the performance measure itself and prove that the use of an erroneus performance measure can lead to misleading results on the evaluation of different methods
Glaudin, Lilian. "Stratégies multicouche, avec mémoire, et à métrique variable en méthodes de point fixe pour l'éclatement d'opérateurs monotones et l'optimisation." Thesis, Sorbonne université, 2019. http://www.theses.fr/2019SORUS119.
Full textSeveral apparently unrelated strategies coexist to implement algorithms for solving monotone inclusions in Hilbert spaces. We propose a synthetic framework for fixed point construction which makes it possible to capture various algorithmic approaches, clarify and generalize their asymptotic behavior, and design new iterative schemes for nonlinear analysis and convex optimization. Our methodology, which is anchored on an averaged quasinonexpansive operator composition model, allows us to advance the theory of fixed point algorithms on several fronts, and to impact their application fields. Numerical examples are provided in the context of image restoration, where we propose a new viewpoint on the formulation of variational problems
Fontaine, Allyx. "Analyses et preuves formelles d'algorithmes distribués probabilistes." Thesis, Bordeaux, 2014. http://www.theses.fr/2014BORD0091/document.
Full textProbabilistic algorithms are simple to formulate. However, theiranalysis can become very complex, especially in the field of distributedcomputing. We present algorithms - optimal in terms of bit complexityand solving the problems of MIS and maximal matching in rings - that followthe same scheme.We develop a method that unifies the bit complexitylower bound results to solve MIS, maximal matching and coloration problems.The complexity of these analyses, which can easily lead to errors,together with the existence of many models depending on implicit assumptionsmotivated us to formally model the probabilistic distributed algorithmscorresponding to our model (message passing, anonymous andsynchronous). Our aim is to formally prove the properties related to theiranalysis. For this purpose, we develop a library, called RDA, based on theCoq proof assistant
Dementiev, Roman. "Algorithm engineering for large data sets hardware, software, algorithms." Saarbrücken VDM, Müller, 2006. http://d-nb.info/986494429/04.
Full textDementiev, Roman. "Algorithm engineering for large data sets : hardware, software, algorithms /." Saarbrücken : VDM-Verl. Dr. Müller, 2007. http://deposit.d-nb.de/cgi-bin/dokserv?id=3029033&prov=M&dok_var=1&dok_ext=htm.
Full textKhungurn, Pramook. "Shirayanagi-Sweedler algebraic algorithm stabilization and polynomial GCD algorithms." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/41662.
Full textIncludes bibliographical references (p. 71-72).
Shirayanagi and Sweedler [12] proved that a large class of algorithms on the reals can be modified slightly so that they also work correctly on floating-point numbers. Their main theorem states that, for each input, there exists a precision, called the minimum converging precision (MCP), at and beyond which the modified "stabilized" algorithm follows the same sequence of steps as the original "exact" algorithm. In this thesis, we study the MCP of two algorithms for finding the greatest common divisor of two univariate polynomials with real coefficients: the Euclidean algorithm, and an algorithm based on QR-factorization. We show that, if the coefficients of the input polynomials are allowed to be any computable numbers, then the MCPs of the two algorithms are not computable, implying that there are no "simple" bounding functions for the MCP of all pairs of real polynomials. For the Euclidean algorithm, we derive upper bounds on the MCP for pairs of polynomials whose coefficients are members of Z, 0, Z[6], and Q[6] where ( is a real algebraic integer. The bounds are quadratic in the degrees of the input polynomials or worse. For the QR-factorization algorithm, we derive a bound on the minimal precision at and beyond which the stabilized algorithm gives a polynomial with the same degree as that of the exact GCD, and another bound on the the minimal precision at and beyond which the algorithm gives a polynomial with the same support as that of the exact GCD. The bounds are linear in (1) the degree of the polynomial and (2) the sum of the logarithm of diagonal entries of matrix R in the QR factorization of the Sylvester matrix of the input polynomials.
by Pramook Khungurn.
M.Eng.
Johansson, Björn, and Emil Österberg. "Algorithms for Large Matrix Multiplications : Assessment of Strassen's Algorithm." Thesis, KTH, Skolan för teknikvetenskap (SCI), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-230742.
Full textStrassen’s algorithm was one of the breakthroughs in matrix analysis in 1968. In this report the thesis of Volker Strassen’s algorithm for matrix multipli- cations along with theories about precisions will be shown. The benefits of using this algorithm compared to naive matrix multiplication and its implica- tions, how its performance compare to the naive algorithm, will be displayed. Strassen’s algorithm will also be assessed on how the output differ when the matrix sizes grow larger, as well as how the theoretical complexity of the al- gorithm differs from the achieved complexity. The studies found that Strassen’s algorithm outperformed the naive matrix multiplication at matrix sizes 1024 1024 and above. The achieved complex- ity was a little higher compared to Volker Strassen’s theoretical. The optimal precision for this case were the double precision, Float64. How the algorithm is implemented in code matters for its performance. A number of techniques need to be considered in order to improve Strassen’s algorithm, optimizing its termination criterion, the manner by which it is padded in order to make it more usable for recursive application and the way it is implemented e.g. parallel computing. Even tough it could be proved that Strassen’s algorithm outperformed the Naive after reaching a certain matrix size, it is still not the most efficient one; e.g. as shown with Strassen-Winograd. One need to be careful of how the sub-matrices are being allocated, to not use unnecessary memory. For further reading one can study cache-oblivious and cache-aware algorithms.
Abergel, Rémy. "Quelques modèles mathématiques et algorithmes rapides pour le traitement d’images." Thesis, Sorbonne Paris Cité, 2016. http://www.theses.fr/2016USPCB051/document.
Full textIn this thesis, we focus on several mathematical models dedicated to low-level digital image processing tasks. Mathematics can be used to design innovative models and to provide some rigorous studies of properties of the produced images. However, those models sometimes involve some intensive algorithms with high computational complexity. We take a special care in developing fast algorithms from the considered mathematical models. First, we give a concise description of some fundamental results of convex analysis based on Legendre-Fenchel duality. Those mathematical tools are particularly efficient to perform the minimization of convex and nonsmooth energies, such as those involving the total variation functional which is used in many image processing applications. Then, we focus on a Fourier-based discretization scheme of the total variation, called Shannon total variation, which provides a subpixellic control of the image regularity. In particular, we show that, contrary to the classically used discretization schemes of the total variation based on finite differences, the use of the Shannon total variation yields images that can be easily interpolated. We also show that this model provides some improvements in terms of isotropy and grid invariance, and propose a new restoration model which transforms an image into a very similar one that can be easily interpolated. Next, we propose an adaptation of the TV-ICE (Total Variation Iterated Conditional Expectations) model, recently proposed by Louchet and Moisan in 2014, to address the restoration of images corrupted by a Poisson noise. We derive an explicit form of the recursion operator involved by this scheme, and show linear convergence of the algorithm, as well as the absence of staircasing effect for the produced images. We also show that this variant involves the numerical evaluation of a generalized incomplete gamma function which must be carefully handled due to the numerical errors inherent to the finite precision floating-point calculus. Then, we propose an fast algorithm dedicated to the evaluation of this generalized 4 incomplete gamma function, and show that the accuracy achieved by the proposed procedure is near optimal for a large range of parameters. Lastly, we focus on the astre (A contrario Smooth TRajectory Extraction) algorithm, proposed by Primet and Moisan in 2011 to perform trajectory detection from a noisy point set sequence. We propose a variant of this algorithm, called cutastre, which manages to break the quadratic complexity of astre with respect to the number of frames of the sequence, while showing similar (and even slightly better) detection performances and preserving some interesting theoretical properties of the original astre algorithm
Knauer, Christian. "Algorithms for comparing geometric patterns (Algorithmen zum Vergleich geometrischer Muster) /." [S.l. : s.n.], 2001. http://www.diss.fu-berlin.de/2002/110/index.html.
Full textVallot, Delphine. "Reconstruction adaptative optimisée pour la quantification en tomographie de positons couplée à un tomodensitomètre." Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30188.
Full textThis study was initiated to evaluate an iterative reconstruction algorithm in positron emission tomography based on a regularization method to obtain convergence. Our aim was to assess its performance, in comparison with other currently available algorithms and to study the impact of the only parameter available to users for eventual optimization, both using anthropomorphic phantoms and clinical data. We confirm that this algorithm shows several advantages compared to the traditional OSEM-MLEM concerning noise, contrast and detectability. By using anthropomorphic phantoms and with access to more reconstruction parameters, the performance could be further improved to decrease the artefacts and the overestimation of certain metrics. Work in progress
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.
Full textCommittee 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.
Pochet, Juliette. "Evaluation de performance d’une ligne ferroviaire suburbaine partiellement équipée d’un automatisme CBTC." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLC005.
Full textIn high-density area, the demand for railway transportation is continuously increasing. Operating companies turn to new intelligent signaling and control systems, such as Communication Based Train Control (CBTC) systems previously deployed on underground systems only. CBTC systems operate trains in automatic pilot and lead to increase the line capacity without expensive modification of infrastructures. They can also include a supervision module in charge of adapting train behavior according to operating objectives and to disturbances, increasing line robustness. In the literature of real-time traffic management, various methods have been proposed to supervise and reschedule trains, on the one hand for underground systems, on the other hand for railway systems. Making the most of the state-of-the-art in both fields, the presented work intend to contribute to the design of supervision and rescheduling functions of CBTC systems operating suburban railway systems. Our approach starts by designing a supervision module for a standard CBTC system. Then, we propose a rescheduling method based on a model predictive control approach and a multi-objective optimization of automatic train commands. In order to evaluate the performances of a railway system, it is necessary to use a microscopic simulation tool including a CBTC model. In this thesis, we present the tool developed by SNCF and named SIMONE. It allows realistic simulation of a railway system and a CBTC system, in terms of functional architecture and dynamics. The presented work has been directly involved in the design and implementation of the tool. Eventually, the proposed rescheduling method was tested with the tool SIMONE on disturbed scenarios. The proposed method was compared to a simple heuristic strategy intending to recover delays. The proposed multi-objective method is able to provide good solutions to the rescheduling problem and over-performs the simple strategy in most cases, with an acceptable process time. We conclude with interesting perspectives for future work
Sauerland, Volkmar [Verfasser]. "Algorithm Engineering for some Complex Practise Problems : Exact Algorithms, Heuristics and Hybrid Evolutionary Algorithms / Volkmar Sauerland." Kiel : Universitätsbibliothek Kiel, 2012. http://d-nb.info/1026442745/34.
Full textAuger, Nicolas. "Analyse réaliste d'algorithmes standards." Thesis, Paris Est, 2018. http://www.theses.fr/2018PESC1110/document.
Full textAt first, we were interested in TimSort, a sorting algorithm which was designed in 2002, at a time where it was hard to imagine new results on sorting. Although it is used in many programming languages, the efficiency of this algorithm has not been studied formally before our work. The fine-grain study of TimSort leads us to take into account, in our theoretical models, some modern features of computer architecture. In particular, we propose a study of the mechanisms of branch prediction. This theoretical analysis allows us to design variants of some elementary algorithms (like binary search or exponentiation by squaring) that rely on this feature to achieve better performance on recent computers. Even if uniform distributions are usually considered for the average case analysis of algorithms, it may not be the best framework for studying sorting algorithms. The choice of using TimSort in many programming languages as Java and Python is probably driven by its efficiency on almost-sorted input. To conclude this dissertation, we propose a mathematical model of non-uniform distribution on permutations, for which permutations that are almost sorted are more likely, and provide a detailed probabilistic analysis
Pontoizeau, Thomas. "Community detection : computational complexity and approximation." Thesis, Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLED007/document.
Full textThis thesis deals with community detection in the context of social networks. A social network can be modeled by a graph in which vertices represent members, and edges represent relationships. In particular, I study four different definitions of a community. First, a community structure can be defined as a partition of the vertices such that each vertex has a greater proportion of neighbors in its part than in any other part. This definition can be adapted in order to study only one community. Then, a community can be viewed as a subgraph in which every two vertices are at distance 2 in this subgraph. Finally, in the context of online meetup services, I investigate a definition for potential communities in which members do not know each other but are related by their common neighbors. In regard to these proposed definitions, I study computational complexity and approximation within problems that either relate to the existence of such communities or to finding them in graphs
Bournat, Marjorie. "Graceful Degradation and Speculation for Robots in Highly Dynamic Environments." Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS035.
Full textDistributed systems are systems composed of multiple communicant processes cooperating to solve a common task. This is a generic model for numerous real systems as wired or mobile networks, shared-memory multiprocessor systems, and so on. From an algorithmic point of view, it is well-known that strong assumptions (as asynchronism or mobility) on such systems lead often to impossibility results or high lower bounds on complexity. In this thesis, we study algorithms that adapt themselves to their environment (i.e., the union of all assumptions on the system) by focusing on the two following approaches. Graceful degradation circumvents impossibility results by degrading the properties offered by the algorithm as the environment become stronger. Speculation allows to bypass high lower bounds on complexity by optimizing the algorithm only on more probable environments. Robot networks are a particular case of distributed systems where processes are endowed with sensors and able to move from a location to another. We consider dynamic environments in which this ability may evolve with time. This thesis answers positively to the open question whether it is possible and attractive to apply gracefully degrading and speculative approaches to robot networks in dynamic environments. This answer is obtained through contributions on gracefully degrading gathering (where all robots have to meet on the same location in finite time) and on speculative perpetual exploration (where robots must visit infinitely often each location)
Rafique, Abid. "Communication optimization in iterative numerical algorithms : an algorithm-architecture interaction." Thesis, Imperial College London, 2014. http://hdl.handle.net/10044/1/17837.
Full textLegay, Sylvain. "Quelques problèmes d'algorithmique et combinatoires en théorie des grapphes." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS030/document.
Full textThis thesis is about graph theory. Formally, a graph is a set of vertices and a set of edges, which are pair of vertices, linking vertices. This thesis deals with various decision problem linked to the notion of graph, and, for each of these problem, try to find its complexity class, or to give an algorithm. The first chapter is about the problem of finding the smallest connected tropical subgraph of a vertex-colored graph, which is the smallest connecter subgraph containing every colors. The second chapter is about problems of tropical homomorphism, a generalization of coloring problem. A link between these problems and several other class of homomorphism problems can be found in this chapter, especially with the class of Constraint Satisfaction Problem. The third chapter is about two variant of the domination problem, namely the global alliance problems in a weighted graph and the safe set problem. The fourth chapter is about the problem of finding a star tree-decomposition, which is a tree-decomposition where the radius of bags is 1. Finally, the fifth chapter is about a variant of the problem of deciding the asymptotic behavior of the iterated biclique graph
Hachimi, Hanaa. "Hybridations d'algorithmes métaheuristiques en optimisation globale et leurs applications." Phd thesis, INSA de Rouen, 2013. http://tel.archives-ouvertes.fr/tel-00905604.
Full textViolich, Stephen Scott. "Fusing Loopless Algorithms for Combinatorial Generation." Thesis, University of Canterbury. Computer Science and Software Engineering, 2006. http://hdl.handle.net/10092/1075.
Full textLavault, Christian. "Algorithmique et complexité distribuées : applications à quelques problèmes fondamentaux de complexité, protocoles distribués à consensus, information globale, problèmes distribués d'élection et de routage." Paris 11, 1987. http://www.theses.fr/1987PA112392.
Full textLashermes, Ronan. "Etude de la sécurité des implémentations de couplage." Thesis, Versailles-St Quentin en Yvelines, 2014. http://www.theses.fr/2014VERS0021/document.
Full textPairings are cryptographic algorithms allowing new protocols for public-key cryptography. After a decade of research which led to a dramatic improvement of the computation speed of pairings, we focused on the security of pairing implementations.For that purpose, we evaluated the resistance to fault attacks. We have sent electromagnetic pulses in the chip computing a pairing at a precise instant. It allowed us to recover the cryptographic secret which should be protected in the computation. Our study was both theoretical and practical; we did implement actual fault attacks. Finally, we proposed countermeasures in order to protect the algorithm in the future
Tchvagha, Zeine Ahmed. "Contribution à l’optimisation multi-objectifs sous contraintes : applications à la mécanique des structures." Thesis, Normandie, 2018. http://www.theses.fr/2018NORMIR13/document.
Full textThe objective of this thesis is the development of multi-objective optimization methods for solving mechanical design problems. Indeed, most of the real problems in the field of mechanical structures have several objectives that are often antagonistic. For example, it is about designing structures by optimizing their weight, their size, and their production costs. The goal of multi-objective optimization methods is the search for compromise solutions between objectives given the impossibility to satisfy all simultaneously. Metaheuristics are optimization methods capable of solving multi-objective optimization problems in a reasonable calculation time without guaranteeing the optimality of the solution (s). In recent years, these algorithms have been successfully applied to solve the problem of structural mechanics. In this thesis, two metaheuristics have been developed for the resolution of multi-objective optimization problems in general and of mechanical structures design in particular. The first algorithm called MOBSA used the crossover and mutation operators of the BSA algorithm. The second one named NNIA+X is a hybridization of an immune algorithm and three crossover inspired by the original crossover operator of the BSA algorithm. To evaluate the effectiveness and efficiency of these two algorithms, tests on some problems in literature have been made with a comparison with algorithms well known in the field of multi-objective optimization. The comparison results using metrics widely used in the literature have shown that our two algorithms can compete with their predecessors
Mhedhbi, Imen. "Ordonnancement d'ateliers de traitements de surfaces pour une production mono-robot/multi-produits : Résolution et étude de la robustesse." Thesis, Ecole centrale de Lille, 2011. http://www.theses.fr/2011ECLI0004/document.
Full textIn this thesis we study the automated electroplating lines. In these lines, the products are immerged in different tanks. The processing times are bounded. The lower bound represents the minimum time to treat the product while the upper bound depends on the treatment.A classical objective is to find the robot moves which minimize the cycle time, this is called ”hoist scheduling problem” (HSP). In this thesis, we study particularly the single-hoist/multi-products.In this direction, three approaches are presented to solve the single-hoist/multi-products problem with introducing the hoist moves time: constraints satisfaction algorithm based on non standard criteria witch the hoist wait time, hybridization with classical heuristics improving the obtained results, and finally the genetic algorithm to optimize the cycle time. Robustness’ notions are finally exploited in the presence of a disturbance at the critical resource of the workshop which is the hoist.The systematic determination of a robust scheduling has been conducted successfully introducing new performance indicators and by applying a multicriteria evaluation method
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.
Full textSigrist, Zoé. "Contribution à l'identification de systèmes non-linéaires en milieu bruité pour la modélisation de structures mécaniques soumises à des excitations vibratoires." Thesis, Bordeaux 1, 2012. http://www.theses.fr/2012BOR14655/document.
Full textThis PhD deals with the caracterisation of mechanical structures, by its structural parameters, when only noisy observations disturbed by additive measurement noises, assumed to be zero-mean white and Gaussian, are available. For this purpose, we suggest using discrete-time models with distinct linear and nonlinear parts. The first one allows the structural parameters to be retrieved whereas the second one gives information on the nonlinearity. When dealing with non-recursive Volterra series, we propose an errors-in-variables (EIV) method to jointly estimate the noise variances and the Volterra kernels. We also suggest a modified unbiased LMS algorithm to estimate the model parameters provided that the input-noise variance is known. When dealing with recursive polynomial model, we propose two methods using evolutionary algorithms. The first includes a stop protocol that takes into account the output-noise variance. In the second one, the fitness functions are based on correlation criteria in which the noise influence is removed or compensated
Douib, Ameur. "Algorithmes bio-inspirés pour la traduction automatique statistique." Thesis, Université de Lorraine, 2019. http://www.theses.fr/2019LORR0005/document.
Full textDifferent components of statistical machine translation systems are considered as optimization problems. Indeed, the learning of the translation model, the decoding and the optimization of the weights of the log-linear function are three important optimization problems. Knowing how to define the right algorithms to solve them is one of the most important tasks in order to build an efficient translation system. Several optimization algorithms are proposed to deal with decoder optimization problems. They are combined to solve, on the one hand, the decoding problem that produces a translation in the target language for each source sentence, on the other hand, to solve the problem of optimizing the weights of the combined scores in the log-linear function to fix the translation evaluation function during the decoding. The reference system in statistical translation is based on a beam-search algorithm for the decoding, and a line search algorithm for optimizing the weights associated to the scores. We propose a new statistical translation system with a decoder entirely based on genetic algorithms. Genetic algorithms are bio-inspired optimization algorithms that simulate the natural process of evolution of species. They allow to handle a set of solutions through several iterations to converge towards optimal solutions. This work allows us to study the efficiency of the genetic algorithms for machine translation. The originality of our work is the proposition of two algorithms: a genetic algorithm, called GAMaT, as a decoder for a phrase-based machine translation system, and a second genetic algorithm, called GAWO, for optimizing the weights of the log-linear function in order to use it as a fitness function for GAMaT. We propose also, a neuronal approach to define a new fitness function for GAMaT. This approach consists in using a neural network to learn a function that combines several scores, which evaluate different aspects of a translation hypothesis, previously combined in the log-linear function, and that predicts the BLEU score of this translation hypothesis. This work allowed us to propose a new machine translation system with a decoder entirely based on genetic algorithms
Delaplace, Claire. "Algorithmes d'algèbre linéaire pour la cryptographie." Thesis, Rennes 1, 2018. http://www.theses.fr/2018REN1S045/document.
Full textIn this thesis, we discuss algorithmic aspects of three different problems, related to cryptography. The first part is devoted to sparse linear algebra. We present a new Gaussian elimination algorithm for sparse matrices whose coefficients are exact, along with a new pivots selection heuristic, which make the whole procedure particularly efficient in some cases. The second part treats with a variant of the Birthday Problem with three lists. This problem, which we call 3XOR problem, intuitively consists in finding three uniformly random bit-strings of fixed length, such that their XOR is the zero string. We discuss practical considerations arising from this problem, and propose a new algorithm which is faster in theory as well as in practice than previous ones. The third part is related to the learning with errors (LWE) problem. This problem is known for being one of the main hard problems on which lattice-based cryptography relies. We first introduce a pseudorandom generator, based on the de-randomised learning with rounding variant of LWE, whose running time is competitive with AES. Second, we present a variant of LWE over the ring of integers. We show that in this case the problem is easier to solve, and we propose an interesting application, revisiting a side-channel attack against the BLISS signature scheme
Niedermeier, Rolf. "Invitation to fixed-parameter algorithms /." Oxford [u.a.] : Oxford Univ. Press, 2006. http://www.gbv.de/dms/ilmenau/toc/500666768niede.PDF.
Full textGuedj, Michaël. "BSP algorithms for LTL & CTL model checking of security protocols." Thesis, Paris Est, 2012. http://www.theses.fr/2012PEST1081.
Full textIn a world strongly dependent on distributed data communication, the design of secure infrastructures is a crucial task. Distributed systems and networks are becoming increasingly important, as most of the services and opportunities that characterise the modern society are based on these technologies. Communication among agents over networks has therefore acquired a great deal of research interest. In order to provide effective and reliable means of communication, more and more communication protocols are invented, and for most of them, security is a significant goal
Kostrygin, Anatolii. "Precise Analysis of Epidemic Algorithms." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLX042/document.
Full textEpidemic algorithms are distributed algorithms in which the agents in thenetwork involve peers similarly to the spread of epidemics. In this work, we focus on randomized rumor spreading -- a class of epidemic algorithms based on the paradigm that nodes call random neighbors and exchange information with these contacts. Randomized rumor spreading has found numerous applications from the consistency maintenance of replicated databases to newsspreading in social networks. Numerous mathematical analyses of different rumor spreading algorithms can be found in the literature. Some of them provide extremely sharp estimates for the performance of such processes, but most of them are based on the inherent properties of concrete algorithms.We develop new simple and generic method to analyze randomized rumor spreading processes in fully connected networks. In contrast to all previous works, which heavily exploit the precise definition of the process under investigation, we only need to understand the probability and the covariance of the events that uninformed nodes become informed. This universality allows us to easily analyze the classic push, pull, and push-pull protocols both in their pure version and in several variations such as when messages fail with constant probability or when nodes call a random number of others each round. Some dynamic models can be analyzed as well, e.g., when the network is a random graph sampled independently each round [Clementi et al. (ESA 2013)]. Despite this generality, our method determines the expected rumor spreading time precisely apart from additive constants, which is more precise than almost all previous works. We also prove tail bounds showing that a deviation from the expectation by more than an additive number of r rounds occurs with probability at most exp(−Ω(r)).We further use our method to discuss the common assumption that nodes can answer any number of incoming calls. We observe that the restriction that only one call can be answered leads to a significant increase of the runtime of the push-pull protocol. In particular, the double logarithmic end phase of the process now takes logarithmic time. This also increases the message complexity from the asymptotically optimal Θ(n log log n) [Karp, Shenker, Schindelhauer, Vöcking (FOCS 2000)] to Θ(n log n). We propose a simple variation of the push-pull protocol that reverts back to the double logarithmic end phase and thus to the Θ(n log log n) message complexity
Gambardella, Luca Maria. "Coupling ant colony system with local search." Doctoral thesis, Universite Libre de Bruxelles, 2015. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209045.
Full textDoctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished
Vialette, Stéphane. "Algorithmic Contributions to Computational Molecular Biology." Habilitation à diriger des recherches, Université Paris-Est, 2010. http://tel.archives-ouvertes.fr/tel-00862069.
Full textGodichon-Baggioni, Antoine. "Algorithmes stochastiques pour la statistique robuste en grande dimension." Thesis, Dijon, 2016. http://www.theses.fr/2016DIJOS053/document.
Full textThis thesis focus on stochastic algorithms in high dimension as well as their application in robust statistics. In what follows, the expression high dimension may be used when the the size of the studied sample is large or when the variables we consider take values in high dimensional spaces (not necessarily finite). In order to analyze these kind of data, it can be interesting to consider algorithms which are fast, which do not need to store all the data, and which allow to update easily the estimates. In large sample of high dimensional data, outliers detection is often complicated. Nevertheless, these outliers, even if they are not many, can strongly disturb simple indicators like the mean and the covariance. We will focus on robust estimates, which are not too much sensitive to outliers.In a first part, we are interested in the recursive estimation of the geometric median, which is a robust indicator of location which can so be preferred to the mean when a part of the studied data is contaminated. For this purpose, we introduce a Robbins-Monro algorithm as well as its averaged version, before building non asymptotic confidence balls for these estimates, and exhibiting their $L^{p}$ and almost sure rates of convergence.In a second part, we focus on the estimation of the Median Covariation Matrix (MCM), which is a robust dispersion indicator linked to the geometric median. Furthermore, if the studied variable has a symmetric law, this indicator has the same eigenvectors as the covariance matrix. This last property represent a real interest to study the MCM, especially for Robust Principal Component Analysis. We so introduce a recursive algorithm which enables us to estimate simultaneously the geometric median, the MCM, and its $q$ main eigenvectors. We give, in a first time, the strong consistency of the estimators of the MCM, before exhibiting their rates of convergence in quadratic mean.In a third part, in the light of the work on the estimates of the median and of the Median Covariation Matrix, we exhibit the almost sure and $L^{p}$ rates of convergence of averaged stochastic gradient algorithms in Hilbert spaces, with less restrictive assumptions than in the literature. Then, two applications in robust statistics are given: estimation of the geometric quantiles and application in robust logistic regression.In the last part, we aim to fit a sphere on a noisy points cloud spread around a complete or truncated sphere. More precisely, we consider a random variable with a truncated spherical distribution, and we want to estimate its center as well as its radius. In this aim, we introduce a projected stochastic gradient algorithm and its averaged version. We establish the strong consistency of these estimators as well as their rates of convergence in quadratic mean. Finally, the asymptotic normality of the averaged algorithm is given
Jartoux, Bruno. "On combinatorial approximation algorithms in geometry." Thesis, Paris Est, 2018. http://www.theses.fr/2018PESC1078/document.
Full textThe analysis of approximation techniques is a key topic in computational geometry, both for practical and theoretical reasons. In this thesis we discuss sampling tools for geometric structures and geometric approximation algorithms in combinatorial optimization. Part I focuses on the combinatorics of geometric set systems. We start by discussing packing problems in set systems, including extensions of a lemma of Haussler, mainly the so-called shallow packing lemma. For said lemma we also give an optimal lower bound that had been conjectured but not established in previous work on the topic. Then we use this lemma, together with the recently introduced polynomial partitioning technique, to study a combinatorial analogue of the Macbeath regions from convex geometry: Mnets, for which we unify previous existence results and upper bounds, and also give some lower bounds. We highlight their connection with epsilon-nets, staples of computational and combinatorial geometry, for example by observing that the unweighted epsilon-net bound of Chan et al. (SODA 2012) or Varadarajan (STOC 2010) follows directly from our results on Mnets. Part II deals with local-search techniques applied to geometric restrictions of classical combinatorial optimization problems. Over the last ten years such techniques have produced the first polynomial-time approximation schemes for various problems, such as that of computing a minimum-sized hitting set for a collection of input disks from a set of input points. In fact, it was shown that for many of these problems, local search with radius Θ(1/epsilon²) gives a (1 + epsilon)-approximation with running time n^{O(1/epsilon²)}. However the question of whether the exponent of n could be decreased to o(1/epsilon²) was left open. We answer it in the negative: the approximation guarantee of local search cannot be improved for any of these problems. The key ingredient is a new lower bound on locally expanding planar graphs, which is then used to show the impossibility results
Kang, Seunghwa. "On the design of architecture-aware algorithms for emerging applications." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/39503.
Full textLin, Han-Hsuan. "Topics in quantum algorithms : adiabatic algorithm, quantum money, and bomb query complexity." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/99300.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 111-115).
In this thesis, I present three results on quantum algorithms and their complexity. The first one is a numerical study on the quantum adiabatic algorithm( QAA) . We tested the performance of the QAA on random instances of MAX 2-SAT on 20 qubits and showed 3 strategics that improved QAA's performance, including a counter intuitive strategy of decreasing the overall evolution time. The second result is a security proof for the quantum money by knots proposed by Farhi et. al. We proved that quantum money by knots can not be cloned in a black box way unless graph isomorphism is efficiently solvable by a quantum computer. Lastly we defined a modified quantum query model, which we called bomb query complexity B(J), inspired by the Elitzur-Vaidman bomb-testing problem. We completely characterized bomb query complexity be showing that B(f) = [Theta](Q(f)2 ). This result implies a new method to find upper bounds on quantum query complexity, which we applied on the maximum bipartite matching problem to get an algorithm with O(n1.75) quantum query complexity, improving from the best known trivial O(n2 ) upper bound.
by Han-Hsuan Lin.
Ph. D.
Renaud, Yoan. "Quelques aspects algorithmiques sur les systèmes de fermeture." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2008. http://tel.archives-ouvertes.fr/tel-00731341.
Full textGrishchenko, Dmitry. "Optimisation proximale avec réduction automatique de dimension." Thesis, Université Grenoble Alpes, 2020. http://www.theses.fr/2020GRALM055.
Full textIn this thesis, we develop a framework to reduce the dimensionality of composite optimization problems with sparsity inducing regularizers. Based on the identification property of proximal methods, we first develop a ``sketch-and-project'' method that uses projections based on the structure of the correct point. This method allows to work with random low-dimensional subspaces instead of considering the full space in the cases when the final solution is sparse. Second, we place ourselves in the context of the delay-tolerant asynchronous proximal methods and use our dimension reduction technique to decrease the total size of communications. However, this technique is proven to converge only for well-conditioned problems both in theory in practice.Thus, we investigate wrapping it up into a proximal reconditioning framework. This leads to a theoretically backed algorithm that is guaranteed to cost less in terms of communications compared with a non-sparsified version; we show in practice that it implies faster runtime convergence when the sparsity of the problem is sufficiently big
Liu, Yong Chun. "Un détecteur perceptif de la hauteur tonale pour la parole téléphonique /." Thèse, Chicoutimi : Université du Québec à Chicoutimi, 1992. http://theses.uqac.ca.
Full textZois, Georgios. "Algorithmic problems in power management of computing systems." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066462/document.
Full textThis thesis is focused on energy-efficient algorithms for job scheduling problems on speed-scalable processors, as well as on processors operating under a thermal and cooling mechanism, where, for a given budget of energy or a thermal threshold, the goal is to optimize a Quality of Service criterion. A part of our research concerns scheduling problems arising in large-data processing environments. In this context, we focus on the MapReduce paradigm and we consider problems of energy-efficient scheduling on multiple speed-scalable processors as well as classical scheduling on a set of unrelated processors.First, we propose complexity results, optimal and constant competitive algorithms for different energy-aware variants of the problem of minimizing the maximum lateness of a set of jobs on a single speed-scalable processor. Then, we consider energy-aware MapReduce scheduling as well as classical MapReduce scheduling (where energy is not our concern) on unrelated processors, where the goal is to minimize the total weighted completion time of a set of MapReduce jobs. We study special cases and generalizations of both problems and propose constant approximation algorithms. Finally, we study temperature-aware scheduling on a single processor that operates under a strict thermal threshold, where each job has its own heat contribution and the goal is to maximize the schedule's throughput. We consider the case of unit-length jobs with a common deadline and we study the approximability of the problem
Mirzazadeh, Mehdi. "Adaptive Comparison-Based Algorithms for Evaluating Set Queries." Thesis, University of Waterloo, 2004. http://hdl.handle.net/10012/1147.
Full textDutta, Himanshu Shekhar. "Survey of Approximation Algorithms for Set Cover Problem." Thesis, University of North Texas, 2009. https://digital.library.unt.edu/ark:/67531/metadc12118/.
Full textDodo, Meva. "Etude de l'apport de la visualisation 3D interactive pour l'administration de systèmes complexe." Toulouse 3, 2008. http://thesesups.ups-tlse.fr/358/.
Full textThe aim of this thesis is to study new methods which allow to improve the understanding of complex systems' structure and to analyze the various events generated by its resources. Three-dimensional techniques are proposed to easy the analysis of the structure of complex systems. A new algorithm for drawing, in 3D, large graphs is proposed in order to optimize the layout of a complex structure. Our method is based on the optimization of the force-directed placement algorithm (FDP) that allows effectively and aesthetically displaying large graphs. Our second approach is to propose metaphors that allow to easily understand the different events generated by devices. This approach is based on the three attributes that define an event: "what, when, where", and it is associated with filtering techniques that choose interesting events according to the management needs
Bedrat, Amina. "G4-Hunter : un nouvel algorithme pour la prédiction des G-quadruplexes." Thesis, Bordeaux, 2015. http://www.theses.fr/2015BORD0197/document.
Full textBiologically relevant G4 DNA structures are formed throughout the genome including immunoglobulin switch regions, promoter sequences and telomeric repeats. They can arise when single-stranded G-rich DNA or RNA sequences are exposed during replication, transcription or recombination. Computational analysis using predictive algorithms suggests that the human genome contains approximately 370 000 potential G4-forming sequences. These predictions are generally limited to the standard G3+N(1−7)G3+N(1−7)G3+N(1−7)G3+ description. However, many stable G4s defy this description and escape this consensus; this is the reason why broadening this description should allow the prediction of more G4 loci. We propose an objective score function, G4- hunter, which predicts G4 folding propensity from a linear nucleic acid sequence. The new method focus on guanines clusters and GC asymmetry, taking into account the whole genomic region rather than individual quadruplexes sequences. In parallel with this computational technique, a large scale in vitro experimental work has also been developed to validate the performance of our algorithm in silico on one hundred of different sequences. G4- hunter exhibits unprecedented accuracy and sensitivity and leads us to reevaluate significantly the number of G4-prone sequences in the human genome. G4-hunter also allowed us to predict potential G4 sequences in HIV and Dictyostelium discoideum, which could not be identified by previous computational methods
Neou, Both Emerite. "Permutation pattern matching." Thesis, Paris Est, 2017. http://www.theses.fr/2017PESC1239/document.
Full textThis thesis focuses on permutation pattern matching problem, which askswhether a pattern occurs in a text where both the pattern and text are permutations.In other words, we seek to determine whether there exist elements ofthe text such that they are sorted and appear in the same order as the elementsof the pattern. The problem is NP-complete. This thesis examines particularcases of the problem that are polynomial-time solvable.For this purpose, we study the problem by giving constraints on the permutationstext and/or pattern. In particular, the cases in which the text and/orpattern are permutations in which the patterns 2413 and 3142 do not occur(also known as separable permutations) and in which the text and/or patternare permutations in which the patterns 213 and 231 do not occur (also known aswedge permutations) are also considered. Some problems related to the patternmatching and the permutation pattern matching with bivincular pattern arealso studied