On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming

We present a primal-dual interior-point algorithm with a filter line-search method for nonlinear programming. Local and global convergence properties of this method were analyzed in previous work. Here we provide a comprehensive description of the algorithm, including the feasibility restoration phase for the filter method, second-order corrections, and inertia correction of the KKT matrix. Heuristics are also considered that allow faster performance. This method has been implemented in the IPOPT code, which we demonstrate in a detailed numerical study based on 954 problems from the CUTEr test set.An evaluation is made of several line-search options, and a comparison is provided with two state-of-the-art interior-point codes for nonlinear programming. Key words. Nonlinear programming

• Type: Journal
• Year: 2006
• Where: MP
• Authors: Andreas Wächter, Lorenz T. Biegler
• Keywords: Filter Line-search Method, MP 2006, Nonlinear Programming, Primal-dual Interior-point Algorithm