A gradient-related algorithm with inexact line searches
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Publication:596214
DOI10.1016/j.cam.2003.10.025zbMath1050.65061OpenAlexW2075234876MaRDI QIDQ596214
Publication date: 10 August 2004
Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.cam.2003.10.025
unconstrained optimizationconvergenceinexact line searchfeasible direction methodgradient-related algorithm
Related Items (11)
Convergence of algorithms in optimization and solutions of nonlinear equations ⋮ The convergence of subspace trust region methods ⋮ New conjugate gradient-like methods for unconstrained optimization ⋮ Nonmonotone adaptive trust region method ⋮ Convergence of memory gradient methods ⋮ Memory gradient method for multiobjective optimization ⋮ CONVERGENCE PROPERTY AND MODIFICATIONS OF A MEMORY GRADIENT METHOD ⋮ On memory gradient method with trust region for unconstrained optimization ⋮ A new trust region method with adaptive radius ⋮ A new super-memory gradient method with curve search rule ⋮ A memory gradient method for non-smooth convex optimization
Cites Work
- Stepsize analysis for descent methods
- Enlarging the region of convergence of Newton's method for constrained optimization
- Supermemory descent methods for unconstrained minimization
- Global convergence result for conjugate gradient methods
- Optimization. Algorithms and consistent approximations
- A globally convergent version of the Polak-Ribière conjugate gradient method
- Introduction to global optimization
- A class of gradient unconstrained minimization algorithms with adaptive stepsize
- A class on nonmonotone stabilization methods in unconstrained optimization
- Memory gradient method for the minimization of functions
- Relation between the memory gradient method and the Fletcher-Reeves method
- Study on a supermemory gradient method for the minimization of functions
- Quadratically convergent algorithms and one-dimensional search schemes
- Global Convergence Properties of Conjugate Gradient Methods for Optimization
- Conjugate Gradient Methods with Inexact Searches
- Numerical Optimization
- Convergence properties of the Fletcher-Reeves method
- A Nonlinear Conjugate Gradient Method with a Strong Global Convergence Property
- Function minimization by conjugate gradients
- The conjugate gradient method in extremal problems
- Conjugate Directions without Linear Searches
- Methods of conjugate gradients for solving linear systems
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