A quasi-Newton method with Cholesky factorization
Copyright policy )A quasi-Newton method with Cholesky factorization
A quasi-Newton method for unconstrained minimization is presented, which uses a Cholesky factorization of an approximation to the Hessian matrix. In each step a new row and column of this approximation matrix is determined and its Cholesky factorization is updated. This reduces storage requirements and simplifies the calculation of the search direction. Precautions are taken to hold the approximation matrix positive definite. It is shown that under usual conditions the method converges superlinearly or evenn-step quadratic.
- University of Stuttgart Germany
quasi-Newton methods, Numerical optimization and variational techniques, minimizing a function, gradient evaluations, Numerical computation of solutions to systems of equations, approximation of the Hessian, Goldstein-Price method, Cholesky factorization
quasi-Newton methods, Numerical optimization and variational techniques, minimizing a function, gradient evaluations, Numerical computation of solutions to systems of equations, approximation of the Hessian, Goldstein-Price method, Cholesky factorization
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