Line Search Filter Methods for Nonlinear Programming: Motivation and Global Convergence

By Andreas Wächter, Lorenz T. Biegler. SIAM Journal on Optimization, 2005

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acados—a modular open-source framework for fast embedded optimal control (2019, background): “merit functions [59] and filter based line search methods [93] for use in a fully converged setting is subject of future work.”
On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming (2006, methodology): “1 The global convergence proof in [26] requires that the eigenvalues of the projection are uniformly bounded away from zero.”
Numerical lower bound shakedown analysis of engineering structures (2011, methodology): “Among the different approaches for the solution of nonlinear optimization problems, we choose the widely used interior-point method [8–11], which has been implemented into several software packages for general nonlinear programming, such as LOQO [12,13], KNITRO [14,15] and IPOPT [16,17].”
A General-Purpose Software Framework for Dynamic Optimization (Een algemene softwareomgeving voor dynamische optimalisatie) (2013, methodology): “Wächter and Biegler [180, 181] then adopted this approach to a filter line-search method which did not suffer from the problem of selecting a penalty parameter in the merit function.”
Shakedown analysis of engineering structures with limited kinematical hardening (2012, methodology): “Based on this method there exist powerful algorithms, such as IPOPT (Wächter and Biegler, 2005; Wächter and Biegler, 2006), KNITRO (Byrd et al.”