Result: New iterative conjugate gradient method for nonlinear unconstrained optimization

Title:
New iterative conjugate gradient method for nonlinear unconstrained optimization
Authors:
Sabrina Ben Hanachi, Badreddine Sellami, Mohammed Belloufi
Source:
RAIRO - Operations Research. 56:2315-2327
Publisher Information:
EDP Sciences, 2022.
Publication Year:
2022
Subject Terms:
Artificial neural network, Artificial intelligence, Convex Optimization, Nonlinear conjugate gradient method, Economics, Computational Mechanics, 0211 other engineering and technologies, Geometry, Conjugate residual method, 02 engineering and technology, Conjugate gradient method, Proximal Gradient Methods, Mathematical analysis, 01 natural sciences, Engineering, Gradient method, Computer security, 0103 physical sciences, FOS: Mathematics, Economic growth, Conjugate, Numerical Analysis, Gradient descent, Numerical Optimization Techniques, RADIUS, Mathematical optimization, Iterative Algorithms for Nonlinear Operators and Optimization, Derivation of the conjugate gradient method, Theory and Applications of Compressed Sensing, Applied mathematics, Computer science, Convex optimization, Algorithm, Regular polygon, Line search, Computational Theory and Mathematics, Physical Sciences, Computer Science, Derivative-Free Optimization, Convergence (economics), Mathematics
Document Type:
Academic journal Article<br />Other literature type
ISSN:
2804-7303
0399-0559
DOI:
10.1051/ro/2022109
DOI:
10.60692/j6zzn-qcp87
DOI:
10.60692/1pwxx-zd073
Rights:
CC BY
Accession Number:
edsair.doi.dedup.....1aa42f5bf9b5f3cef74d6d1a1b185cbc
Database:
OpenAIRE

Further Information

Conjugate gradient methods (CG) are an important class of methods for solving unconstrained optimization problems, especially for large-scale problems. Recently, they have been much studied. In this paper, we propose a new conjugate gradient method for unconstrained optimization. This method is a convex combination of Fletcher and Reeves (abbreviated FR), Polak–Ribiere–Polyak (abbreviated PRP) and Dai and Yuan (abbreviated DY) methods. The new conjugate gradient methods with the Wolfe line search is shown to ensure the descent property of each search direction. Some general convergence results are also established for this method. The numerical experiments are done to test the efficiency of the proposed method, which confirms its promising potentials.