A new hybrid CGM for unconstrained optimization problems
H. A. Wasi, Mushtak A. K. Shiker
Abstract
Abstract In this work, a hybrid CGM (conjugate gradient method) has been suggested to solve the unconstrained optimization problems by combining a (Polak– Ribiére–Polyak) method with (Fletcher-Reeves) method. The suggested method has the sufficient descent property under the suggestion of a suitable line search and appropriate conditions. The global convergence is construct for this method. The numerical results display that this method is better than the other method comparing with.
Topics & Concepts
Conjugate gradient methodConvergence (economics)Line searchMathematical optimizationDescent (aeronautics)Computer scienceNonlinear conjugate gradient methodGradient descentConstruct (python library)Property (philosophy)AlgorithmMathematicsArtificial intelligenceEngineeringArtificial neural networkEpistemologyPhilosophyRADIUSEconomicsComputer securityProgramming languageAerospace engineeringEconomic growthAdvanced Optimization Algorithms ResearchIterative Methods for Nonlinear EquationsOptimization and Variational Analysis