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- W4319868529 abstract "Decentralized decision-making can be represented as a connected decision network of agents collaboratively optimizing their local objective functions over common coupling constraints. In this setting, solving large-scale mathematical programming centrally is undesirable or impossible because the data storage and decision authority are already decentralized, the communication bandwidth for information exchange is limited, and privacy concerns with information may exist. We introduce a taxonomy of mathematical programming-based decentralized optimization problems and decentralized algorithms based on the degree of information sharing, information exchange and existence of a central coordinator. We synthesize the literature and identify the shortcomings of a decentralized algorithm, the trends, and the potential research directions based on the proposed taxonomy." @default.
- W4319868529 created "2023-02-11" @default.
- W4319868529 creator A5088761904 @default.
- W4319868529 date "2023-05-01" @default.
- W4319868529 modified "2023-09-25" @default.
- W4319868529 title "A review of decentralized optimization focused on information flows of decomposition algorithms" @default.
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- W4319868529 doi "https://doi.org/10.1016/j.cor.2023.106190" @default.
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