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Showing 1 to 14 of 14 for “"dual decomposition"”.
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Gradient-Based Distributed Model Predictive Control
… problem in distributed fashion using dual decomposition, which is a well-known method. Dual decomposition is traditionally used in conjunction with (sub)gradient methods which are known to have bad convergence rate properties, especially for ill-conditioned problem. In this thesis it …
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Otimização de redes de distribuição de água: estudo de dois modelos
… solved by implicit enumeration algorithm and by dual decomposition algorithm. The other model seeks optimization of the network by heuristic search of optimal diameters, based on energy costs necessary to elevation of piezometric height of the network source nodes. In case of network supplied by …
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Distributed Newton-type algorithms for network resource allocation
… resource allocation problems rely on using dual decomposition and first-order (gradient or subgradient) methods, which involve simple computations and can be implemented in a distributed manner, yet suffer from slow rate of convergence. Second-order methods are faster, but their direct …
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Distributed Method to Optimal Profile Descent
… is then solved in a decentralized manner using dual decomposition techniques under inter-aircraft ADS-B mechanism. This method divides the optimization problem into more manageable sub-problems which are then distributed to the group of aircraft. Each aircraft solves its assigned sub-problem and …
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Theory and Practice of Large-scale Logistics: Offline Contextual Bandits and Decomposition Methods
… I propose an efficient solution method based on dual decomposition that leverages Lagrangian duality to split the problem into smaller, computationally tractable subproblems. This work bridges the gap between operations research theory and practice, demonstrating how theoretical foundations can …
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Regularization methods on solving Poisson’s equation and Poisson Boltzmann equation with singular charge sources and diffuse interfaces
… equation and PB models. The success lies in a dual decomposition -- besides decomposing the potential into Coulomb and reaction field components, the dielectric function is also split into a constant base plus space changing part. Using the constant dielectric base, the Coulomb potential is …
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Formulations and methods for wind farm layout optimization
… formulations. The second part introduces a dual-decomposition method for getting a close bound on the optimal solutions to discrete formulations, thereby facilitating the use of heuristics by giving an objective estimate of solution quality. The final part presents a robust layout …
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A scalable architecture for the interconnection of microgrids
… India. The model is then formulated as a layered decomposition, in which local scheduling optimization occurs at each microgrid, requiring only nearest neighbor communication to ensure feasibility of the solutions. Finally, a methodology is proposed to generate distributed optimal policies for a …
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Spectral efficiency optimization with channel state information of a massive MIMO System
… of imperfect CSI, an algorithm called penalty dual decomposition (PDD) is proposed for these problems. The PDD is a double-loop iterative algorithm that has a guaranteed convergence to Karush-Kuhn-Tucker (KKT) solution of the hybrid precoding problem under a mild assumption. The KKT solution …
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Renewable energy in electric utility capacity planning: a decomposition approach with application to a Mexican utility
… phase, two algorithms, based on a Lagrangian Dual decomposition and a Generalized Benders Decomposition, are developed. The Lagrangian Dual formulation results in a subproblem which can be separated into single-year plantmix problems that are easily solved using a breakeven analysis. The …
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Two-Stage Stochastic Mixed Integer Nonlinear Programming: Theory, Algorithms, and Applications
… shedding. In the third direction, we develop a dual decomposition approach for solving two-stage stochastic quadratically constrained quadratic mixed integer programs. We also create a new module for an open-source package DSP (Decomposition for Structured Programming) to solve this problem. We …
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Joint-stochastic Spectral Inference for Robust Co-occurrence Modeling and Latent Topic Analysis
… learning low-dimensional geometry into provable decompositions of co-occurrence information, spectral inference provides fast algorithms and optimality guarantees for non-linear dimensionality reduction or latent topic analysis. Spectral approaches reduce the dependence on the original training …
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Efficient energy management in ultra-dense wireless networks
… optimization one. This, combined with Lagrangian dual decomposition, is used to create a distributed solution. After cellassociation and resource allocation phases, the proposed solution in order to further reduce power consumption performs Cell On/Off. Then, by using the computer simulation …
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Modeling and management of dynamic loads in power systems
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2019-08-01