Global convergence of a primal-dual interior-point method for nonlinear programming
Keywords:Interior-point method, primal-dual, convergence analysis
AbstractMany recent convergence results obtained for primal-dual interior-point methods for nonlinear programming, use assumptions of the boundedness of generated iterates. In this paper we replace such assumptions by new assumptions on the NLP problem, develop a modification of a primal-dual interior-point method implemented in software package LOQO and analyze convergence of the new method from any initial guess.
How to Cite
Griva, I., Shanno, D. F., Vanderbei, R. J., & Benson, H. Y. (2008). Global convergence of a primal-dual interior-point method for nonlinear programming. Algorithmic Operations Research, 3(1). Retrieved from https://journals.lib.unb.ca/index.php/AOR/article/view/5665