JOURNAL ARTICLE

Sufficient Descent Condition of the Polak-Ribière-Polyak (PRP) Conjugate Gradient Method without Line Search

Abstract

<p>Nonlinear conjugate gradient methods for unconstrained optimization problems are used in many aspects of theoretical and applied sciences. They are iterative methods, so at any iteration a step length is computed using a method called line search. In most cases, the sufficient descent condition plays an important role to prove the global convergence of a conjugate gradient method. Due to its outperformance in practical computation, the Polak-Ribi&egrave;re-Polyak (PRP) conjugate gradient method is widely used for solving nonlinear unconstrained optimization problems. However, the sufficient descent condition of PRP has not established without line search yet. In this study, we established the sufficient descent condition without line search based on the conditions 0 &lt;&nbsp;<i>b<sub>k</sub><sup>PRP</sup></i>&nbsp;<i>&pound; x b</i><sub><i>k</i></sub><sup><i>FR</i></sup> and 1 &lt;&nbsp;<i>b</i><sub><i>k</i></sub><sup><i>PRP&nbsp;</i></sup><i>&pound;mb<sub>k</sub><sup>FR</sup></i>, where 0 &lt;&nbsp;<i>x</i>&nbsp;&lt; 1 and&nbsp;<i>m</i>&nbsp;&gt; 1. As a result, we found that under certain conditions, the sufficient descent condition is satisfied when the PRP implemented without line search</p>

Keywords:
Nonlinear conjugate gradient method Line search Conjugate gradient method Mathematics Gradient descent Descent (aeronautics) Descent direction Conjugate residual method Convergence (economics) Gradient method Line (geometry) Mathematical optimization Applied mathematics Computer science Artificial intelligence Geometry Artificial neural network

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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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