Authors: V. Moraru
Keywords: Quasi-Newton methods, Constrained Optimization, Superlinear convergence.
Abstract
In the present paper the problem of constrained equality optimization is reduced to sequential solving a series of problems of quadratic programming. The Hessian of the Lagrangian is approximated by a sequence of symmetric positive definite matrices. The matrix approximation is updated at every iteration by a Gram- Schmidt modified algorithm. We establish that methods is locally convergent and the sequence {x
k}converges to the solution a two-step superlinear rate.
Vasile Moraru, Dept. of Computing Mathematics and Programming, Technical University of Moldova
Bd. Stefan cel Mare, 168, Kishinev, 277012, Moldova
Fulltext
–
0.16 Mb