A reduced Hessian algorithm with line search filter method for nonlinear programming

A reduced Hessian algorithm with line search filter method for nonlinear programming

0.00 Avg rating0 Votes
Article ID: iaor20115062
Volume: 217
Issue: 19
Start Page Number: 7679
End Page Number: 7691
Publication Date: Jun 2011
Journal: Applied Mathematics and Computation
Authors: ,
Keywords: line search
Abstract:

This paper proposes a line search filter reduced Hessian method for nonlinear equality constrained optimization. The feature of the presented algorithm is that the reduced Hessian method is used to produce a search direction, a backtracking line search procedure to generate step size, some filtered rules to determine step acceptance, second order correction technique to reduce infeasibility and overcome the Maratos effects. It is shown that this algorithm does not suffer from the Maratos effects by using second order correction step, and under mild assumptions fast convergence to second order sufficient local solutions is achieved. The numerical experiment is reported to show the effectiveness of the proposed algorithm.

Reviews

Required fields are marked *. Your email address will not be published.