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- W4287690908 abstract "We propose a decentralized penalty method for general convex constrained multi-agent optimization problems. Each auxiliary penalized problem is solved approximately with a special parallel descent splitting method. The method can be implemented in a computational network where each agent sends information only to the nearest neighbours. Convergence of the method is established under rather weak assumptions. We also describe a specialization of the proposed approach to the feasibility problem." @default.
- W4287690908 created "2022-07-26" @default.
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- W4287690908 date "2020-08-10" @default.
- W4287690908 modified "2023-10-16" @default.
- W4287690908 title "Decentralized Multi-Agent Optimization Based on a Penalty Method" @default.
- W4287690908 hasPublicationYear "2020" @default.
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