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 9 of 9 for “"Derivative Free Optimization"”.
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Algorithms for Derivative-Free Optimization
… Search (M&S), a new local search algorithm for derivative-free optimization. M&S performs a local search from a given point. The search is guided by identifying descent directions from a quadratic model fitted around the best known point, while using information from other evaluated points. We …
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Derivative-Free Meta-Blackbox Optimization on Manifold
… nonconvex, but potentially similar optimization problems poses a significant computational challenge in various engineering applications. This thesis presents the first meta-learning framework that leverages the shared structure among sequential tasks to improve the computational …
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Técnicas de otimização da produção para reservatórios de petróleo: abordagens sem uso de derivadas para alocação dinâmica das vazões de produção e injeção
… o de Busca Direta em Padrões (Pattern Search), o Derivative Free Optimization de Conn et al e o Algoritmo Genético. Os estudos foram aplicados a dois casos de características distintas. O primeiro caso apresenta características bem simples e de fácil controle. O outro caso de aplicação é um modelo …
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An inverse problem framework for reconstruction of phonon properties using solutions of the Boltzmann transport equation
… The reconstruction is formulated as a non-convex optimization problem whose goal is to minimize the difference between the experimental results and the one calculated by a Boltzmann transport equation (BTE)-based model of the experimental process, with the desired material property treated as the …
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Patterns in an elastic bar
… Method (FEM) to approximate the model and the Derivative Free Optimization (DFO) to find the location of the jump.
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Progress on the Interplay of Machine Learning and Optimization
Machine learning and optimization have been playing significant roles in the world. Despite the remarkable advancements in these fields, various crucial problems remain unsolved. In this thesis, we address some of these problems by exploring the interplay of machine learning and optimization. In …
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A Large Scale Network Model to Obtain Interwell Formation Characteristics
… values between each node are the unknowns. A derivative free optimization algorithm is utilized to minimize the objective function. Knowing the conductivity of each of the bonds, a two phase problem is formulated and solved in this work to obtain the fractional flow at node interfaces and at …
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Derivative-Free Methods for High-Dimensional Optimization with Application to Centrifugal Pump Design
… real-life design problems do not have access to derivative information. For instance, many design problems use open-source or commercial computational fluid dynamics (CFD) simulation codes to evaluate design performance. Although automatic differentiation and adjoints have become increasingly …
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Gradient-Based Sensitivity Analysis with Kernels
… space, which we then use to develop a Bayesian optimization algorithm which can exploit locally important directions.