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SUMMARY:Enhancing Collocation-Based Dynamic Optimization through Adaptive 
 Mesh Refinement - Linus Langenkamp\, Bernhard Bachmann
DTSTART;TZID=Europe/Zurich:20250910T100500
DTEND;TZID=Europe/Zurich:20250910T103000
DTSTAMP:20260811T224149Z
UID:pretalx-16thmodelicafmiconference-K8CECA@pretalx.com
DESCRIPTION:Direct collocation-based dynamic optimization plays an importa
 nt role in the optimization of equation-based models. With this approach\,
  continuous problems are transcribed into sparse nonlinear programs (NLPs)
  that can be solved efficiently. The open-source Modelica environment Open
 Modelica provides an implementation using Radau IIA collocation\, but has 
 major limitations\, such as the lack of parameter optimization\, no adapti
 ve mesh refinement\, and no support for higher-order integration schemes. 
 This paper presents (1) a comprehensive reimplementation that addresses th
 ese limitations and (2) a novel $h$-method mesh refinement algorithm. Impl
 emented in the custom Python / C++ optimization framework GDOPT\, the appr
 oach demonstrates significant performance improvements\, solving typical p
 roblems 2 to 3 times faster than OpenModelica under equivalent conditions.
  Using the proposed mesh refinement algorithm\, the framework correctly id
 entifies non-smooth regions and increases resolution accordingly\, requiri
 ng only a small increase in computation time. The implementation lays the 
 foundation for a future integration into the OpenModelica toolchain.
LOCATION:202
URL:https://pretalx.com/16thmodelicafmiconference/talk/K8CECA/
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