Adjoint-Based Predictor-Corrector Sequential Convex Programming for Parametric Nonlinear Optimization

DOI10.1137/110844349zbMath1273.49040arXiv1109.2800OpenAlexW2059113336MaRDI QIDQ4915166

Carlo Savorgnan, Moritz Diehl, Quoc Tran Dinh

Publication date: 9 April 2013

Published in: SIAM Journal on Optimization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1109.2800

zbMATH Keywords

sequential convex programmingparametric nonlinear programmingadjoint-based optimizationpredictor-corrector path-following approach

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25) Nonlinear programming (90C30) Sensitivity, stability, parametric optimization (90C31) Numerical methods based on nonlinear programming (49M37)

Related Items (9)

Time-distributed optimization for real-time model predictive control: stability, robustness, and constraint satisfaction ⋮ Pathfollowing for parametric mathematical programs with complementarity constraints ⋮ Time-Varying Semidefinite Programming: Path Following a Burer–Monteiro Factorization ⋮ Sequential quadratic programming methods for parametric nonlinear optimization ⋮ Multi-level iterations for economic nonlinear model predictive control ⋮ A Predictor-Corrector Path-Following Algorithm for Dual-Degenerate Parametric Optimization Problems ⋮ Autogenerating microsecond solvers for nonlinear MPC: A tutorial using ACADO integrators ⋮ Multiple Shooting in a Microsecond ⋮ Nonlinear model predictive control with aggregated constraints

Uses Software

• SDPT3
• NewtonLib

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