A consensus algorithm based on collective neurodynamic system for distributed optimization with linear and bound constraints
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Publication:2185684
DOI10.1016/j.neunet.2019.10.008zbMath1440.90050OpenAlexW2981876218WikidataQ91072154 ScholiaQ91072154MaRDI QIDQ2185684
Publication date: 5 June 2020
Published in: Neural Networks (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.neunet.2019.10.008
Related Items (11)
Decentralized proximal splitting algorithms for composite constrained convex optimization ⋮ A continuous-time neurodynamic approach and its discretization for distributed convex optimization over multi-agent systems ⋮ A second-order accelerated neurodynamic approach for distributed convex optimization ⋮ A neurodynamic approach for nonsmooth optimal power consumption of intelligent and connected vehicles ⋮ Decentralized ADMM with compressed and event-triggered communication ⋮ Two-timescale recurrent neural networks for distributed minimax optimization ⋮ Distributed learning for sketched kernel regression ⋮ Resilient penalty function method for distributed constrained optimization under Byzantine attack ⋮ Neurodynamic approaches for multi-agent distributed optimization ⋮ Distributed time-varying optimization control protocol for multi-agent systems via finite-time consensus approach ⋮ A continuous-time consensus algorithm using neurodynamic system for distributed time-varying optimization with inequality constraints
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