The initial release of CUTE, a widely used testing environment for optimization software, was
described by Bongartz, et al.[1995]. A new version, now known as CUTEr, is presented …

This book provides a comprehensive treatment of a very successful class of methods for
solving optimization problems with PDE and inequality constraints as well as variational …

A mechanism for proving global convergence in SQP--filter methods for nonlinear
programming (NLP) is described. Such methods are characterized by their use of …

In this paper, the filter technique of Fletcher and Leyffer (1997) is used to globalize the
primal-dual interior-point algorithm for nonlinear programming, avoiding the use of merit …

A global convergence proof is presented for a class of trust region filter–type methods for
nonlinear programming. Such methods are characterized by their use of the dominance …

Transition to superlinear local convergence is shown for a modified version of the trust-
region filter-SQP method for nonlinear programming introduced by Fletcher, Leyffer, and …

Coordination among vehicular actors becomes increasingly important at the dawn of
autonomous driving. With communication serving as the basis for this process, latency …

A new method is introduced for solving equality constrained nonlinear optimization
problems. This method does not use a penalty function, nor a filter, and yet can be proved to …

A central theme of applied mathematics is the design of accurate mathematical models for a
variety of technical, financial, medical, and many other applications, and the development of …

Inspired by penalty-free approaches for smooth optimization problems, we propose a
sequential linearized proximal gradient method (SLPG) for a class of optimization problems …