JOURNAL ARTICLE

A Modified PRP Conjugate Gradient Algorithm with Trust Region for Optimization Problems

Xiangrong LiQingsong Ruan

Year: 2011 Journal:   Numerical Functional Analysis and Optimization Vol: 32 (5)Pages: 496-506   Publisher: Taylor & Francis

Abstract

In this article, a modified PRP algorithm is presented for unconstrained optimization problems. This method possesses sufficiently descent property and the proposed direction is in a trust region. The global convergence and the linear convergence rate of the given method are established under weaker conditions. Numerical results show that the presented method is effective.

Keywords:
Trust region Conjugate gradient method Mathematics Convergence (economics) Nonlinear conjugate gradient method Descent (aeronautics) Property (philosophy) Mathematical optimization Rate of convergence Gradient descent Algorithm Optimization problem Computer science Artificial intelligence

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6
Cited By
0.45
FWCI (Field Weighted Citation Impact)
36
Refs
0.63
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Citation History

Topics

Advanced Optimization Algorithms Research
Physical Sciences →  Mathematics →  Numerical Analysis
Sparse and Compressive Sensing Techniques
Physical Sciences →  Engineering →  Computational Mechanics
Iterative Methods for Nonlinear Equations
Physical Sciences →  Mathematics →  Numerical Analysis

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