Application of spectral conjugate gradient methods for solving unconstrained optimization problems
Ibrahim Mohammed Sulaiman, Usman Abbas Yakubu, Mustafa Mamat
2020An International Journal of Optimization and Control Theories & Applications (IJOCTA)26 citationsDOIOpen Access PDF
Abstract
Conjugate gradient (CG) methods are among the most efficient numerical methods for solving unconstrained optimization problems. This is due to their simplicty and less computational cost in solving large-scale nonlinear problems. In this paper, we proposed some spectral CG methods using the classical CG search direction. The proposed methods are applied to real-life problems in regression analysis. Their convergence proof was establised under exact line search. Numerical results has shown that the proposed methods are efficient and promising.
Topics & Concepts
Conjugate gradient methodNonlinear conjugate gradient methodLine searchConvergence (economics)Conjugate residual methodMathematical optimizationDerivation of the conjugate gradient methodComputer scienceGradient methodAlgorithmMathematicsNumerical analysisApplied mathematicsGradient descentArtificial intelligenceComputer securityEconomicsMathematical analysisEconomic growthArtificial neural networkRADIUSAdvanced Optimization Algorithms ResearchIterative Methods for Nonlinear EquationsOptimization and Variational Analysis