Litcius/Paper detail

A Liu-Storey-type conjugate gradient method for unconstrained minimization problem with application in motion control

Auwal Bala Abubakar, Maulana Malik, Poom Kumam, Hassan Mohammad, Min Sun, Abdulkarim Hassan Ibrahim, Aliyu Ibrahim Kiri

2022Journal of King Saud University - Science28 citationsDOIOpen Access PDF

Abstract

Conjugate gradient methods have played a vital role in finding the minimizers of large-scale unconstrained optimization problems due to the simplicity of their iteration, convergence properties and their low memory requirements. Based on the Liu-Storey conjugate gradient method, in this paper, we present a Liu-Storey type method for finding the minimizers of large-scale unconstrained optimization problems. The direction of the proposed method is constructed in such a way that the sufficient descent condition is satisfied. Furthermore, we establish the global convergence result of the method under the standard Wolfe and Armijo-like line searches. Numerical findings indicate that our presented approach is efficient and robust in solving large-scale test problems. In addition, an application of the method is explored.

Topics & Concepts

Conjugate gradient methodConvergence (economics)Nonlinear conjugate gradient methodGradient descentGradient methodScale (ratio)MathematicsMathematical optimizationMinificationLine searchConjugate residual methodDescent (aeronautics)Derivation of the conjugate gradient methodComputer scienceApplied mathematicsArtificial neural networkArtificial intelligenceAerospace engineeringComputer securityEngineeringEconomic growthRADIUSEconomicsQuantum mechanicsPhysicsAdvanced Optimization Algorithms ResearchOptimization and Variational AnalysisSparse and Compressive Sensing Techniques
A Liu-Storey-type conjugate gradient method for unconstrained minimization problem with application in motion control | Litcius