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Distributed continuous-time optimization for convex problems with coupling linear inequality constraints

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  • Oleg O. Khamisov

    (Skolkovo Institute of Science and Technology)

Abstract

In this paper we propose a novel distributed continuous-time algorithm aimed to solve optimization problems with cost function being a sum of local strictly convex multidimensional functions associated to individual agents. Additionally, the problems can have coupled equality and inequality constraints. We prove global asymptotic convergence of the algorithm for a connected graph topology. In order to investigate its practical implementation, we analyze convergence when Euler method is applied to represent discrete-time communication. Finally, we support our results with numerical experiments of the developed approach application for power balancing in New England power system.

Suggested Citation

  • Oleg O. Khamisov, 2024. "Distributed continuous-time optimization for convex problems with coupling linear inequality constraints," Computational Management Science, Springer, vol. 21(1), pages 1-20, June.
    • Handle: RePEc:spr:comgts:v:21:y:2024:i:1:d:10.1007_s10287-024-00501-6
    DOI: 10.1007/s10287-024-00501-6
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    References listed on IDEAS

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    1. Jens Hübner & Martin Schmidt & Marc C. Steinbach, 2020. "Optimization techniques for tree-structured nonlinear problems," Computational Management Science, Springer, vol. 17(3), pages 409-436, October.
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    Cited by:

    1. Panos Pardalos & Valery Kalyagin & Mario R. Guarracino, 2024. "Editorial," Computational Management Science, Springer, vol. 21(1), pages 1-5, June.

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