Autors:

CiteWeb id: 20060000184

CiteWeb score: 2675

DOI: 10.1007/s10107-004-0559-y

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.

The publication "On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming" is placed in the Top 10000 of the best publications in CiteWeb. Also in the category Mathematics it is included to the Top 1000. Additionally, the publicaiton "On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming" is placed in the Top 1000 among other scientific works published in 2006.
Links to full text of the publication: