A new predictor–corrector method for solving unconstrained minimization problems

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود 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

Solving Large Scale Unconstrained Minimization Problems by a New ODE Numerical Integration Method

In reference [1], for large scale nonlinear equations   = 0 F X , a new ODE solving method was given. This paper is a continuous work. Here   F X has gradient structure i.e.    =  F X f  X ,   f X is a scalar function. The eigenvalues of the Jacobian of   F X , or the Hessian of   f X , are all real number. So the new method is very suitable for this structure. For quadratic fun...

متن کامل

A New Method for Solving Constraint Satisfaction Problems

Many important problems in Artificial Intelligence can be defined as Constraint Satisfaction Problems (CSP). These types of problems are defined by a limited set of variables, each having a limited domain and a number of Constraints on the values of those variables (these problems are also called Consistent Labeling Problems (CLP), in which “Labeling" means assigning a value to a variable.) Sol...

متن کامل

A New Method for Solving Constraint Satisfaction Problems

Many important problems in Artificial Intelligence can be defined as Constraint Satisfaction Problems (CSP). These types of problems are defined by a limited set of variables, each having a limited domain and a number of Constraints on the values of those variables (these problems are also called Consistent Labeling Problems (CLP), in which “Labeling means assigning a value to a variable.) Solu...

متن کامل

A Free Line Search Steepest Descent Method for Solving Unconstrained Optimization Problems

In this paper, we solve unconstrained optimization problem using a free line search steepest descent method. First, we propose a double parameter scaled quasi Newton formula for calculating an approximation of the Hessian matrix. The approximation obtained from this formula is a positive definite matrix that is satisfied in the standard secant relation. We also show that the largest eigen value...

متن کامل

A regularized limited-memory BFGS method for unconstrained minimization problems

The limited-memory BFGS (L-BFGS) algorithm is a popular method of solving large-scale unconstrained minimization problems. Since LBFGS conducts a line search with the Wolfe condition, it may require many function evaluations for ill-posed problems. To overcome this difficulty, we propose a method that combines L-BFGS with the regularized Newton method. The computational cost for a single iterat...

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: Journal of Computational and Applied Mathematics

سال: 1986

ISSN: 0377-0427

DOI: 10.1016/0377-0427(86)90005-1