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A class of distributed optimization methods with event-triggered communication

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Listed:
  • Martin Meinel
  • Michael Ulbrich
  • Sebastian Albrecht

Abstract

We present a class of methods for distributed optimization with event-triggered communication. To this end, we extend Nesterov’s first order scheme to use event-triggered communication in a networked environment. We then apply this approach to generalize the proximal center algorithm (PCA) for separable convex programs by Necoara and Suykens. Our method uses dual decomposition and applies the developed event-triggered version of Nesterov’s scheme to update the dual multipliers. The approach is shown to be well suited for solving the active optimal power flow (DC-OPF) problem in parallel with event-triggered and local communication. Numerical results for the IEEE 57 bus and IEEE 118 bus test cases confirm that approximate solutions can be obtained with significantly less communication while satisfying the same accuracy estimates as solutions computed without event-triggered communication. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Martin Meinel & Michael Ulbrich & Sebastian Albrecht, 2014. "A class of distributed optimization methods with event-triggered communication," Computational Optimization and Applications, Springer, vol. 57(3), pages 517-553, April.
    • Handle: RePEc:spr:coopap:v:57:y:2014:i:3:p:517-553
    DOI: 10.1007/s10589-013-9609-9
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    References listed on IDEAS

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    1. Sun, Junjie & Tesfatsion, Leigh, 2006. "DC Optimal Power Flow Formulation and Solution Using QuadProgJ," Working Papers 18221, Iowa State University, Department of Economics.
    2. NESTEROV, Yu., 2005. "Smooth minimization of non-smooth functions," LIDAM Reprints CORE 1819, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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