A nonmonotone line search technique for Newton's method
SIAM Journal on Numerical Analysis
Projected gradient methods for linearly constrained problems
Mathematical Programming: Series A and B
Global convergence of a class of trust region algorithms for optimization with simple bounds
SIAM Journal on Numerical Analysis
A limited memory algorithm for bound constrained optimization
SIAM Journal on Scientific Computing
The Barzilai and Borwein Gradient Method for the Large Scale Unconstrained Minimization Problem
SIAM Journal on Optimization
Nonmonotone Spectral Projected Gradient Methods on Convex Sets
SIAM Journal on Optimization
An Active Set Newton Algorithm for Large-Scale Nonlinear Programs with Box Constraints
SIAM Journal on Optimization
Large-Scale Active-Set Box-Constrained Optimization Method with Spectral Projected Gradients
Computational Optimization and Applications
Projected Barzilai-Borwein methods for large-scale box-constrained quadratic programming
Numerische Mathematik
A New Active Set Algorithm for Box Constrained Optimization
SIAM Journal on Optimization
Convergence properties of nonmonotone spectral projected gradient methods
Journal of Computational and Applied Mathematics
| Hi-index | 7.29 |
In this paper, we consider a multivariate spectral projected gradient (MSPG) method for bound constrained optimization. Combined with a quasi-Newton property, the multivariate spectral projected gradient method allows an individual adaptive step size along each coordinate direction. On the basis of nonmonotone line search, global convergence is established. A numerical comparison with the traditional SPG method shows that the method is promising.