Preconditioning Newton–Krylov methods in nonconvex large scale optimization

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Preconditioning Newton-Krylov methods in nonconvex large scale optimization

We consider an iterative preconditioning technique for large scale optimization, where the objective function is possibly non-convex. First, we refer to the solution of a generic indefinite linear system by means of a Krylov subspace method, and describe the iterative construction of the preconditioner which does not involve matrices products or matrix storage. The set of directions generated b...

متن کامل

Inertia-Revealing Preconditioning For Large-Scale Nonconvex Constrained Optimization

Fast nonlinear programming methods following the all-at-once approach usually employ Newton’s method for solving linearized Karush-Kuhn-Tucker (KKT) systems. In nonconvex problems, the Newton direction is only guaranteed to be a descent direction if the Hessian of the Lagrange function is positive definite on the nullspace of the active constraints, otherwise some modifications to Newton’s meth...

متن کامل

Preconditioning Indefinite Systems in Interior Point Methods for Large Scale Linear Optimization

We discuss the use of preconditioned conjugate gradients method for solving the reduced KKT systems arising in interior point algorithms for linear programming. The (indefinite) augmented system form of this linear system has a number of advantages, notably a higher degree of sparsity than the (positive definite) normal equations form. Therefore we use the conjugate gradients method to solve th...

متن کامل

Dynamic scaling based preconditioning for truncated Newton methods in large scale unconstrained optimization

This paper deals with the preconditioning of truncated Newton methods for the solution of large scale nonlinear unconstrained optimization problems. We focus on preconditioners which can be naturally embedded in the framework of truncated Newton methods, i.e. which can be built without storing the Hessian matrix of the function to be minimized, but only based upon information on the Hessian obt...

متن کامل

Quasi-Newton Methods for Nonconvex Constrained Multiobjective Optimization

Here, a quasi-Newton algorithm for constrained multiobjective optimization is proposed. Under suitable assumptions, global convergence of the algorithm is established.

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Computational Optimization and Applications

سال: 2013

ISSN: 0926-6003,1573-2894

DOI: 10.1007/s10589-013-9563-6