Publication | Open Access
Global convergence properties of a new class of conjugate gradient method for unconstrained optimization
23
Citations
18
References
2014
Year
Mathematical ProgrammingNumerical AnalysisEngineeringContinuous OptimizationNew FormulaNonlinear Conjugate GradientDerivative-free OptimizationNew ClassInverse ProblemsExact Line SearchNonlinear OptimizationGlobal Convergence PropertiesUnconstrained OptimizationNondifferentiable OptimizationApproximation TheoryConvergence Analysis
Nonlinear conjugate gradient (CG) methods are widely used for solving large scale unconstrained optimization problems. Many studies have been devoted to modified and improve this method. In this paper, a new parameter of CG method that possesses global convergence properties using exact line search is proposed. Numerical results show that the new formula is best and more efficient when compared with the other classical CG methods
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