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Showing 1 to 7 of 7 for “"Subgradient Method."”.

  1. Recovery of primal solution in dual subgradient schemes

    … problems. In particular, we employ the subgradient method to solve the Lagrangian dual of a convex constrained problem, and use a primal-averaging scheme to obtain near-optimal and near-feasible primal solutions. We numerically evaluate the performance of the scheme in the framework of …

    mit Repository record for Recovery of primal solution in dual subgradient schemes (opens in a new tab)

  2. Distributed online algorithms for energy management in smart grids

    … for distributed economic dispatch based on Subgradient method and Alternating Direction Method of Multipliers (ADMM), both designed to be agnostic with any initialization vector. The proposed distributed online solutions leverage a dynamic average consensus algorithm to track the …

    utc Repository record for Distributed online algorithms for energy management in smart grids (opens in a new tab)

  3. Optimisation models and algorithms for multicast message routing and power control in wireless multihop networks

    … coupled structure of the problem. We implement a subgradient method for solving the dual problem, and then look at ways to accelerate its convergence. We also investigate the behaviour and convergence of a simple but effective primal co-ordinate descent method before numerically investigating its …

    birmingham Repository record for Optimisation models and algorithms for multicast message routing and power control in wireless multihop networks (opens in a new tab)

  4. Accelerated first-order optimization methods using inertia and error bounds

    … applications. The focus is on first-order methods which have low per-iteration complexity and can exploit problem structure to a high degree. First-order methods have the capacity to address large-scale problems for which all alternative methods fail. However, first-order methods can take …

    uiuc Repository record for Accelerated first-order optimization methods using inertia and error bounds (opens in a new tab)

  5. Asymptotic Behaviour and Derivation of Mean Field Models

    … behaviour of the Arrow-Hurwicz-Uzawa gradient method, which is a dynamical system for locating saddle points of concave-convex functions. This method is widely used in distributed optimisation over networks, for example in power systems and in rate control in communication networks. Chapter 3 …

    cambridge Repository record for Asymptotic Behaviour and Derivation of Mean Field Models (opens in a new tab)

  6. Exploratory research of Lagrangian relaxation for cloud workflow scheduling

    Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms

    uiuc Repository record for Exploratory research of Lagrangian relaxation for cloud workflow scheduling (opens in a new tab)

  7. Nondifferentiable Optimization of Lagrangian Dual Formulations for Linear Programs with Recovery of Primal Solutions

    … which simplex as well as interior point based methods can tend to be ineffective. In contrast, Lagrangian relaxation or dual formulations, when applied in concert with suitable primal recovery strategies, have the potential for providing quick bounds as well as enabling useful branching …

    vt Repository record for Nondifferentiable Optimization of Lagrangian Dual Formulations for Linear Programs with Recovery of Primal Solutions (opens in a new tab)