A nonmonotonic trust region method for constrained optimization problems
نویسندگان
چکیده
منابع مشابه
Outer Trust-Region Method for Constrained Optimization
Given an algorithm A for solving some mathematical problem based on the iterative solution of simpler subproblems, an Outer Trust-Region (OTR) modification of A is the result of adding a trust-region constraint to each subproblem. The trust-region size is adaptively updated according to the behavior of crucial variables. The new subproblems should not be more complex than the original ones and ...
متن کاملA filter-trust-region method for simple-bound constrained optimization
In this paper we propose a filter-trust-region algorithm for solving nonlinear optimization problems with simple bounds. It extends the technique of Gould, Sainvitu and Toint [15] designed for unconstrained optimization. The two main ingredients of the method are a filter-trust-region algorithm and the use of a gradient-projection method. The algorithm is shown to be globally convergent to at l...
متن کاملA trust region algorithm for constrained optimization
We review the main techniques used in trust region algorithms for nonlinear constrained optimization. 1. Trust Region Idea Constrained optimization is to minimize a function subject to finitely many algebraic equation and inequality conditions. It has the following form
متن کاملAn augmented Lagrangian trust region method for equality constrained optimization
In this talk, we present a trust region method for solving equality constrained optimization problems, which is motivated by the famous augmented Lagrangian function. It is different from standard augmented Lagrangian methods where the augmented Lagrangian function is minimized at each iteration. This method, for fixed Lagrange multiplier and penalty parameters, tries to minimize an approximate...
متن کاملConvergence to a Second-order Point of a Trust-region Algorithm with a Nonmonotonic Penalty Parameter for Constrained Optimization Convergence to a Second-order Point of a Trust-region Algorithm with a Nonmonotonic Penalty Parameter for Constrained Optimization 1
A Abstract In a recent paper, the author (Ref. 1) proposed a trust-region algorithm for solving the problem of minimizing a non-linear function subject to a set of equality constraints. The main feature of the algorithm is that the penalty parameter in the merit function can be decreased whenever it is warranted. He studied the behavior of the penalty parameter and proved several global and loc...
متن کاملذخیره 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: The Journal of the Australian Mathematical Society. Series B. Applied Mathematics
سال: 1999
ISSN: 0334-2700,1839-4078
DOI: 10.1017/s0334270000010626