3 papers
math.OC2025
An Interior-Point Algorithm for Continuous Nonlinearly Constrained Optimization with Noisy Function and Derivative Evaluations
Frank E. Curtis, Shima Dezfulian, Andreas Waechter
An algorithm based on the interior-point methodology for solving continuous nonlinearly constrained optimization problems is proposed, analyzed, and tested. The distinguishing feat…
math.OC2024
On the Convergence of Interior-Point Methods for Bound-Constrained Nonlinear Optimization Problems with Noise
Shima Dezfulian, Andreas Wächter
We analyze the convergence properties of a modified barrier method for solving bound-constrained optimization problems where evaluations of the objective function and its derivativ…
math.OC2022
Derivative-Free Bound-Constrained Optimization for Solving Structured Problems with Surrogate Models
Frank E. Curtis, Shima Dezfulian, Andreas Wächter
We propose and analyze a model-based derivative-free (DFO) algorithm for solving bound-constrained optimization problems where the objective function is the composition of a smooth…