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Distributed Multiobjective Optimization for Network Resource Allocation of Multiagent Systems.
IEEE Trans Cybern ; 51(12): 5800-5810, 2021 Dec.
Article em En | MEDLINE | ID: mdl-31940585
In this article, a distributed multiobjective optimization problem is formulated for the resource allocation of network-connected multiagent systems. The framework encompasses a group of distributed decision makers in the subagents, where each of them possesses a local preference index. Novel distributed algorithms are proposed to solve such a problem in a distributed manner. The weighted Lp preference index is utilized in each agent since it can provide a robust Pareto solution to the problem. By using distributed fixed-time optimization methods, the Lp preference index is constructed online without specifying the unknown parameters. Then, it is proved that the problem admits a unique Pareto solution. By exploiting consensus and gradient descent techniques, asymptotic convergence to the optimal solution is established via Lyapunov theories. Distinct from most of the current works, the proposed framework does not require any prior information in the formulation process, and private data can be well protected using this distributed approach. Numerical examples are included to validate the effectiveness of the proposed algorithms.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: IEEE Trans Cybern Ano de publicação: 2021 Tipo de documento: Article País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: IEEE Trans Cybern Ano de publicação: 2021 Tipo de documento: Article País de publicação: Estados Unidos