Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 26 for “"globally convergent"”.
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MULTI-MODEL ALGORITHMS FOR OPTIMIZATION (TRUST REGIONS, NONLINEAR LEAST SQUARES, SECANT, HYBRID METHODS, MODEL SWITCHING)
… First, essentially any multi-model algorithm is globally convergent if each of the models is sufficiently well behaved. Second, algorithms based on the central feature of the NL2SOL switching system are globally convergent if one model is well behaved and each other model obeys a "sufficient …
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Preconditioned sequential and parallel conjugate gradient algorithms for homotopy curve tracking
… of nonlinear systems of equations that are globally convergent for almost all starting points, i.e., with probability one. The essence of all such algorithms is the construction of an appropriate homotopy map and then tracking some smooth curve in the zero set of this homotopy map. HOMPACK …
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Parallel Sparse Linear Algebra for Homotopy Methods
Globally convergent homotopy methods are used to solve difficult nonlinear systems of equations by tracking the zero curve of a homotopy map. Homotopy curve tracking involves solving a sequence of linear systems, which often vary greatly in difficulty. In this research, a popular iterative solution …
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An augmented Jacobian matrix algorithm for tracking homotopy zero curves
… systems of (algebraic) equations that are globally convergent for almost all starting points, i.e., with probability one. The essence of all such algorithms is the construction of an appropriate homotopy map and then tracking some smooth curve in the zero set of this homotopy map. The …
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Reliability diagnostic strategies for series systems under imperfect testing
… Furthermore, the algorithm appears to be globally convergent. Choice of a starting solution affects the rate of convergence, and guidelines for selecting the starting solution were discussed. Implementation of the heuristic was illustrated by numerical example.
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ON SOLVING MULTI-OBJECTIVE SIMULATION OPTIMIZATION BY OPTIMAL COMPUTING BUDGET ALLOCATION AND RANDOM SEARCH
… of large deviation principle. Second, two globally convergent partition-based random search algorithms are developed to solve multi-objective optimization via simulation. Last, a less conservative approach is proposed to attack robust Ranking and Selection with input uncertainty.
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Kernel-Based Interior-Point Algorithms for the Linear Complementarity Problem
… semi-definite matrix M, that the algorithm is globally convergent and has very good convergence properties. For some instances of the eligible kernel functions, the complexity of the algorithm, in terms of the number of iterations, considered in this thesis matches the best complexity results …
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POLSYS_PLP: A Partitioned Linear Product Homotopy Code for Solving Polynomial Systems of Equations
Globally convergent, probability-one homotopy methods have proven to be very effective for finding all the isolated solutions to polynomial systems of equations. After many years of development, homotopy path trackers based on probability-one homotopy methods are reliable and fast. Now, theoretical …
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An augmented Lagrangian algorithm for optimization with equality constraints in Hilbert spaces
… the basic algorithm. In this thesis we discuss a globally convergent augmented Lagrangian algorithm and discretize it in terms of functional analytic restriction operators. Given this setting, we prove global convergence of the discretized version of this algorithm to a stationary point of the …
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Model parameter estimation of atherosclerotic plaque mechanical properties : calculus-based and heuristic algorithms
… multiple regions of far-reaching modulus, is globally convergent, shows immunity to ill-conditioning, and is expandable to more complex material models
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Parallel homotopy curve tracking on a hypercube
… solving non-linear systems of equations that are globally convergent with probability one from an arbitrary starting point. The essence of these algorithms is the construction of an appropriate homotopy map and subsequent tracking of some smooth curve in the zero set of the homotopy map. Tracking …
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Optimization of luminescent solar concentrators
… subjected to an optimization algorithm based on Globally Convergent Method of Moving Asymptotes (GCMMA). For this optimization, the objective function is the integrated flux on the solar cell and the design variable is the absorption coefficient of the dye which in turn gives the spatial dye …
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Probabilistic models and optimization algorithms for large-scale transportation problems
… leads to a discrete SO algorithm that is both globally convergent and has good small sample performance. The proposed algorithm is validated and used to address a high-dimensional car-sharing optimization problem.
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Probability-One Homotopy Maps for Mixed Complementarity Problems
Probability-one homotopy algorithms have strong convergence characteristics under mild assumptions. Such algorithms for mixed complementarity problems (MCPs) have potentially wide impact because MCPs are pervasive in science and engineering. A probability-one homotopy algorithm for MCPs was …
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Familias paramétricas de procesos iterativos de alto orden de convergencia
… case, the iterative methods of the family are globally convergent if the order of convergence is even, and generally convergent if the order of convergence is odd. In the complex plane, we present a study of the convergence from a numerical and dynamical point of view. With the objective of …
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Study of the factors that influence the lubrication of the three-piece oil control ring
… improved by modifying the initial guess of the globally convergent Newton's method. The roughness truncation method was applied to the model to improve the accuracy of the model. A correlation between the integrated hydrodynamic pressure and the rail/liner clearance was developed to replace the …
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Quasi-Newton algorithms for large scale nonlinear systems
… to the solution - a clear validation of the globally convergent property of the double dogleg strategy. Finally, the usefulness of the double dogleg strategy in solving a system of nonlinear equations via the nonlinear least squares approach and in locating multiple equilibrium configurations …
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Adaptive mesh refinement in topology optimization
… These tools are subsequently used to make the Globally Convergent Method of Moving Asymptotes (GCMMA), a popular optimization algorithm in the topology optimization community, mesh independent. We then benchmark our algorithm with three common problems in topology optimization. High resolution …
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Transform learning based image and video processing
… guarantee for this algorithm. It is shown to be globally convergent to the set of partial minimizers of the non-convex learning problem. When applied to images, the algorithm learns a collection of well-conditioned square transforms, and a good clustering of patches or textures. The resulting …
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Fast MRI with sparse sampling: models, algorithms, and applications
… optimization problem, for which we develop a globally convergent algorithm based on the half-quadratic regularization with continuation procedure. We systematically demonstrate the complementary advantages of incorporating both low-rank and sparsity models into the proposed formulation with a …
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