LiftOpt

on this page you find informations about the C++ packages LiftOpt and LiftOptDyn. LiftOpt, developed at the SimOpt Group of the IWR, University of Heidelberg, in collaboration with the OPTEC, KU Leuven, is a toolkit for nonlinear optimization that aims to extend the advantages of multiple shooting to general NLP problems with nearly no additional computational and implementation effort compared to a classic approach. LiftOptDyn, developed at IWR, is also an implementation of the lifting idea, but specifically tailored to the context of optimization problems (optimal control, parameter estimation) involving dynamic models described by differential equations.


References in zbMATH (referenced in 11 articles , 1 standard article )

Showing results 1 to 11 of 11.
Sorted by year (citations)

  1. Quirynen, Rien; Gros, Sébastien; Diehl, Moritz: Inexact Newton-type optimization with iterated sensitivities (2018)
  2. Quirynen, Rien; Gros, Sébastien; Houska, Boris; Diehl, Moritz: Lifted collocation integrators for direct optimal control in ACADO toolkit (2017)
  3. Scholz, Teresa; Raischel, Frank; Lopes, Vitor V.; Lehle, Bernd; Wächter, Matthias; Peinke, Joachim; Lind, Pedro G.: Parameter-free resolution of the superposition of stochastic signals (2017)
  4. Quirynen, Rien; Vukov, Milan; Diehl, Moritz: Multiple shooting in a microsecond (2015)
  5. Quirynen, R.; Vukov, M.; Zanon, M.; Diehl, M.: Autogenerating microsecond solvers for nonlinear MPC: a tutorial using ACADO integrators (2015)
  6. Houska, Boris; Diehl, Moritz: A quadratically convergent inexact SQP method for optimal control of differential algebraic equations (2013)
  7. Sorber, Laurent; Van Barel, Marc; De Lathauwer, Lieven: Optimization-based algorithms for tensor decompositions: canonical polyadic decomposition, decomposition in rank-$(L_r,L_r,1)$ terms, and a new generalization (2013)
  8. Sager, Sebastian; Barth, Carola M.; Diedam, Holger; Engelhart, Michael; Funke, Joachim: Optimization as an analysis tool for human complex problem solving (2011)
  9. Albersmeyer, Jan: Adjoint-based algorithms and numerical methods for sensitivity generation and optimization of large scale dynamic systems. (2010)
  10. Albersmeyer, Jan; Diehl, Moritz: The lifted Newton method and its application in optimization (2009)
  11. Potschka, Andreas: A direct method for the numerical solution of optimization problems with time-periodic PDE constraints. (2001)


Further publications can be found at: http://www.iwr.uni-heidelberg.de/~Jan.Albersmeyer/liftopt/index.php?t=4