Computing subgradients of convex relaxations for solutions of parametric ordinary differential equations

DOI10.1080/10556788.2024.2346641MaRDI QIDQ6661112

Publication date: 10 January 2025

Published in: Optimization Methods \& Software (Search for Journal in Brave)

Nonconvex programming, global optimization (90C26) Nonsmooth analysis (49J52) Inequalities involving derivatives and differential and integral operators (26D10) Numerical methods of relaxation type (49M20)

Cites Work

Title not available (Why is that?)
Title not available (Why is that?)
Title not available (Why is that?)
Title not available (Why is that?)
Title not available (Why is that?)
Title not available (Why is that?)
Improved relaxations for the parametric solutions of ODEs using differential inequalities
Convex envelopes of products of convex and component-wise concave functions
Branch-and-lift algorithm for deterministic global optimization in nonlinear optimal control
Generalized derivatives for solutions of parametric ordinary differential equations with non-differentiable right-hand sides
Reverse propagation of McCormick relaxations
Differentiable McCormick relaxations
Convergence rate of McCormick relaxations
Generalized McCormick relaxations
Convergence-order analysis for differential-inequalities-based bounds and relaxations of the solutions of ODEs
Lectures on convex optimization
Generalized derivatives of differential-algebraic equations
Solution dependence on initial conditions in differential variational inequalities
One-step methods of any order for ordinary differential equations with discontinuous right-hand sides
A bundle-Newton method for nonsmooth unconstrained minimization
Handbook of test problems in local and global optimization
Sensitivity coefficients for discontinuous dynamic systems
A hybrid LP/NLP paradigm for global optimization relaxations
A polyhedral branch-and-cut approach to global optimization
Parametric sensitivity functions for hybrid discrete/continuous systems
Software and algorithms for sensitivity analysis of large-scale differential algebraic systems
Convexification and global optimization in continuous and mixed-integer nonlinear programming. Theory, algorithms, software, and applications
Numerical methods and software for sensitivity analysis of differential-algebraic systems
A branch-and-reduce approach to global optimization
Convex envelopes generated from finitely many compact convex sets
Tighter McCormick relaxations through subgradient propagation
Linearization of McCormick relaxations and hybridization with the auxiliary variable method
Optimization-based convex relaxations for nonconvex parametric systems of ordinary differential equations
Multivariate McCormick relaxations
Methods of descent for nondifferentiable optimization
A nonsmooth version of Newton's method
On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming
Global optimization with nonlinear ordinary differential equations
Lexicographic differentiation of nonsmooth functions
Nonlinear systems.
Nonlinear convex and concave relaxations for the solutions of parametric ODEs
Introduction to Piecewise Differentiable Equations
Adjoint Mode Computation of Subgradients for McCormick Relaxations
Julia: A Fresh Approach to Numerical Computing
Global optimal control with the direct multiple shooting method
On Subdifferentials of Optimal Value Functions
Adjoint Sensitivity Analysis for Nonsmooth Differential-Algebraic Equation Systems
A vector forward mode of automatic differentiation for generalized derivative evaluation
Evaluating Derivatives
McCormick-Based Relaxations of Algorithms
Computability of global solutions to factorable nonconvex programs: Part I — Convex underestimating problems
Directional Derivatives for Extremal-Value Functions with Applications to the Completely Convex Case
Adjoint Sensitivity Analysis for Differential-Algebraic Equations: The Adjoint DAE System and Its Numerical Solution
Branch-locking AD techniques for nonsmooth composite functions and nonsmooth implicit functions
EAGO.jl: easy advanced global optimization in Julia
Generalized Derivatives for Hybrid Systems
An Algorithm for Separable Nonconvex Programming Problems
Convex Analysis
JuMP: A Modeling Language for Mathematical Optimization
A Lipschitz Condition Preserving Extension for a Vector Function
Ordinary differential equations.
Constructing a subgradient from directional derivatives for functions of two variables

This page was built for publication: Computing subgradients of convex relaxations for solutions of parametric ordinary differential equations

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6661112)