Modified active set projected spectral gradient method for bound constrained optimization
نویسندگان
چکیده
منابع مشابه
Practical active-set Euclidian trust-region method with spectral projected gradients for bound-constrained minimization
A practical active-set method for bound-constrained minimization is introduced. Within the current face the classical Euclidian trust-region method is employed. Spectral projected gradient directions are used to abandon faces. Numerical results are presented.
متن کاملSpectral projected gradient method for stochastic optimization
We consider the Spectral Projected Gradient method for solving constrained optimization porblems with the objective function in the form of mathematical expectation. It is assumed that the feasible set is convex, closed and easy to project on. The objective function is approximated by a sequence of Sample Average Approximation functions with different sample sizes. The sample size update is bas...
متن کاملLarge-Scale Active-Set Box-Constrained Optimization Method with Spectral Projected Gradients
A new active-set method for smooth box-constrained minimization is introduced. The algorithm combines an unconstrained method, including a new line-search which aims to add many constraints to the working set at a single iteration, with a recently introduced technique (spectral projected gradient) for dropping constraints from the working set. Global convergence is proved. A computer implementa...
متن کاملA Two-Stage Active-Set Algorithm for Bound-Constrained Optimization
In this paper, we describe a two-stage method for solving optimization problems with bound constraints. It combines the active-set estimate described in [1] with a modification of the nonmonotone line search framework recently proposed in [2]. In the first stage, the algorithm exploits a property of the active-set estimate that ensures a significant reduction of the objective function when sett...
متن کاملInexact projected gradient method for vector optimization
In this work, we propose an inexact projected gradient-like method for solving smooth constrained vector optimization problems. In the unconstrained case, we retrieve the steepest descent method introduced by Graña Drummond and Svaiter. In the constrained setting, the method we present extends the exact one proposed by Graña Drummond and Iusem, since it admits relative errors on the search dire...
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: Applied Mathematical Modelling
سال: 2011
ISSN: 0307-904X
DOI: 10.1016/j.apm.2010.09.011