Corpus ID: 237940840

# A Primal Decomposition Approach to Globally Coupled Aggregative Optimization over Networks

@article{Huang2021APD,
title={A Primal Decomposition Approach to Globally Coupled Aggregative Optimization over Networks},
author={Yuanhanqing Huang and Jianghai Hu},
journal={ArXiv},
year={2021},
volume={abs/2109.12297}
}
• Yuanhanqing Huang, Jianghai Hu
• Published 25 September 2021
• Computer Science, Engineering, Mathematics
• ArXiv
We consider a class of multi-agent optimization problems, where each agent has a local objective function that depends on its own decision variables and the aggregate of others, and is willing to cooperate with other agents to minimize the sum of the local objectives. After associating each agent with an auxiliary variable and the related local estimates, we conduct primal decomposition to the globally coupled problem and reformulate it so that it can be solved distributedly. Based on the… Expand

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