Zuguo He
Abstract
This paper proposes an improved hybrid optimization method for unconstrained optimization.The new method not only can make up the defect of Newton method that requires convex objective function but also possesses global convergence and locally quadratic convergence property under some conditions.Numerical experiments show that the new algorithm is efficient and reasonable.
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This paper proposes an improved hybrid optimization method for unconstrained optimization.The new method not only can make up the defect of Newton method that requires convex objective function but also possesses global convergence and locally quadratic convergence property under some conditions.Numerical experiments show that the new algorithm is efficient and reasonable.
Key concepts: Convergence (economics), Mathematical optimization, Computer science, Property (philosophy), Quadratic programming, Function (biology), Quadratic equation, Convex function