Add to ORKGIn this paper, we propose a modification of the self-scaling quasi-Newton (DFP) method for unconstrained optimization using logistic mapping. We shoe that it produces a positive definite matrix. Numerical results demonstrate that the new algorithm is superior to standard DFP method with respect to the NOI and NOF
In this paper, we investigate quasi-Newton methods for solving unconstrained optimization problems. ...
AbstractThe quasi-Newton family of algorithms for minimizing functions and solving systems of nonlin...
The success of Newton’s method for smooth optimization, when Hessians are available, motivated the i...
In our work, we have proposed a new transformation Biggs's self-scaling Quasi-Newton update which is...
AbstractQuasi-Newton methods update, at each iteration, the existing Hessian approximation (or its i...
summary:A survey note whose aim is to establish the heuristics and natural relations in a class of Q...
This thesis is concerned with analyzing and improving the performance of quasi-Newton methods for f...
AbstractThe secant equation, which underlies all standard ‘quasi-Newton’ minimisation methods, arise...
Quasi-Newton method has been widely used in solving unconstrained optimization problems. The popular...
AbstractMost “quasi-Newton” methods in common use for function minimisation use a quadratic model to...
AbstractA bound on the possible deterioration in the condition number of the inverse Hessian approxi...
AbstractThis paper presents a modified quasi-Newton method for structured unconstrained optimization...
A quasi-Newton method is presented for minimizing a nonlinear function while constraining the variab...
Vita.A transformed Quasi-Newton algorithm has been developed for the optimization of unconstrained f...
Quasi-Newton method has been widely used in solving unconstrained optimization problems. The popular...
In this paper, we investigate quasi-Newton methods for solving unconstrained optimization problems. ...
AbstractThe quasi-Newton family of algorithms for minimizing functions and solving systems of nonlin...
The success of Newton’s method for smooth optimization, when Hessians are available, motivated the i...
In our work, we have proposed a new transformation Biggs's self-scaling Quasi-Newton update which is...
AbstractQuasi-Newton methods update, at each iteration, the existing Hessian approximation (or its i...
summary:A survey note whose aim is to establish the heuristics and natural relations in a class of Q...
This thesis is concerned with analyzing and improving the performance of quasi-Newton methods for f...
AbstractThe secant equation, which underlies all standard ‘quasi-Newton’ minimisation methods, arise...
Quasi-Newton method has been widely used in solving unconstrained optimization problems. The popular...
AbstractMost “quasi-Newton” methods in common use for function minimisation use a quadratic model to...
AbstractA bound on the possible deterioration in the condition number of the inverse Hessian approxi...
AbstractThis paper presents a modified quasi-Newton method for structured unconstrained optimization...
A quasi-Newton method is presented for minimizing a nonlinear function while constraining the variab...
Vita.A transformed Quasi-Newton algorithm has been developed for the optimization of unconstrained f...
Quasi-Newton method has been widely used in solving unconstrained optimization problems. The popular...
In this paper, we investigate quasi-Newton methods for solving unconstrained optimization problems. ...
AbstractThe quasi-Newton family of algorithms for minimizing functions and solving systems of nonlin...
The success of Newton’s method for smooth optimization, when Hessians are available, motivated the i...