Hidden invariant convexity for global and conic-intersection optimality guarantees in discrete-time optimal control

Jorn H. Baayen, Krzysztof Postek

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Abstract

Non-convex discrete-time optimal control problems in, e.g., water or power systems, typically involve a large number of variables related through nonlinear equality constraints. The ideal goal is to find a globally optimal solution, and numerical experience indicates that algorithms aiming for Karush–Kuhn–Tucker points often find solutions that are indistinguishable from global optima. In our paper, we provide a theoretical underpinning for this phenomenon, showing that on a broad class of problems the objective can be shown to be an invariant convex function (invex function) of the control decision variables when state variables are eliminated using implicit function theory. In this way, optimality guarantees can be obtained, the exact nature of which depends on the position of the solution within the feasible set. In a numerical example, we show how high-quality solutions are obtained with local search for a river control problem where invexity holds.

Original languageEnglish
Pages (from-to)263-281
Number of pages19
JournalJournal of Global Optimization
Volume82
Issue number2
DOIs
Publication statusPublished - 2021

Keywords

  • Discrete-time optimal control
  • Global optimality
  • Invexity
  • KKT conditions
  • Optimal control
  • PDE-constrained optimization

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