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Sparse Switching Times Optimization and a Sweeping Hessian Proximal Method

In: Operations Research Proceedings 2019

Author

Listed:
  • Alberto De Marchi

    (Universität der Bundeswehr München)

  • Matthias Gerdts

    (Universität der Bundeswehr München)

Abstract

The switching times optimization problem for switched dynamical systems, with fixed initial state, is considered. A nonnegative cost term for changing dynamics is introduced to induce a sparse switching structure, that is, to reduce the number of switches. To deal with such problems, an inexact Newton-type arc search proximal method, based on a parametric local quadratic model of the cost function, is proposed. Numerical investigations and comparisons on a small-scale benchmark problem are presented and discussed.

Suggested Citation

  • Alberto De Marchi & Matthias Gerdts, 2020. "Sparse Switching Times Optimization and a Sweeping Hessian Proximal Method," Operations Research Proceedings, in: Janis S. Neufeld & Udo Buscher & Rainer Lasch & Dominik Möst & Jörn Schönberger (ed.), Operations Research Proceedings 2019, pages 89-95, Springer.
    • Handle: RePEc:spr:oprchp:978-3-030-48439-2_11
    DOI: 10.1007/978-3-030-48439-2_11
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