In recent years the use of quasi-Newton methods in optimization algorithms has inspired much of the research in an area of numerical linear algebra called updating matrix factorizations. Previous research in this area has been concerned with updating the factorization of a symmetric positive definite matrix. Here, a numerical algorithm is presented for updating the Symmetric Indefinite Factorization of Bunch and Parlett. The algorithm requires only O(n/sup 2/) arithmetic operations to update the factorization of an n x n symmetric matrix when modified by a rank-one matrix. An error analysis of this algorithm is given. Computational results are presented that investigate the timing and accuracy of this algorithm. Another algorithm is presen...
In this paper, we investigate a symmetric rank-one (SR1) quasi-Newton (QN) formula in which the Hess...
AbstractThis paper proposes a new robust and quickly convergent pattern search method based on an im...
AbstractIn this paper, we present a new symmetric rank-one (SR1) method for the solution of unconstr...
In recent years the use of quasi-Newton methods in optimization algorithms has inspired much of the ...
AbstractUnconstrained optimization problems using Newton-type methods sometimes require that the Hes...
Arevised algorithm is given for unconstrained optimization using quasi-Newton methods. The method is...
This thesis is concerned with analyzing and improving the performance of quasi-Newton methods for f...
Quasi-Newton algorithms for unconstrained nonlinear minimization generate a sequence of matrices tha...
AbstractThe quasi-Newton family of algorithms for minimizing functions and solving systems of nonlin...
Abstract: "We propose a quasi-Newton algorithm for solving optimization problems with nonlinear equa...
A stabilized version of the symmetric rank-one updating method for solving unconstrained optimizatio...
In this paper a new class of quasi-Newton methods, namedLQN, is introduced in order to solve unconst...
Abstract This paper is concerned with Newton-like methods for solving unconstrained minimization pro...
Symmetric positive definite matrices appear in most methods for Unconstrained Optimization. The met...
Many methods for solving minimization problems are variants of Newton method, which requires the spe...
In this paper, we investigate a symmetric rank-one (SR1) quasi-Newton (QN) formula in which the Hess...
AbstractThis paper proposes a new robust and quickly convergent pattern search method based on an im...
AbstractIn this paper, we present a new symmetric rank-one (SR1) method for the solution of unconstr...
In recent years the use of quasi-Newton methods in optimization algorithms has inspired much of the ...
AbstractUnconstrained optimization problems using Newton-type methods sometimes require that the Hes...
Arevised algorithm is given for unconstrained optimization using quasi-Newton methods. The method is...
This thesis is concerned with analyzing and improving the performance of quasi-Newton methods for f...
Quasi-Newton algorithms for unconstrained nonlinear minimization generate a sequence of matrices tha...
AbstractThe quasi-Newton family of algorithms for minimizing functions and solving systems of nonlin...
Abstract: "We propose a quasi-Newton algorithm for solving optimization problems with nonlinear equa...
A stabilized version of the symmetric rank-one updating method for solving unconstrained optimizatio...
In this paper a new class of quasi-Newton methods, namedLQN, is introduced in order to solve unconst...
Abstract This paper is concerned with Newton-like methods for solving unconstrained minimization pro...
Symmetric positive definite matrices appear in most methods for Unconstrained Optimization. The met...
Many methods for solving minimization problems are variants of Newton method, which requires the spe...
In this paper, we investigate a symmetric rank-one (SR1) quasi-Newton (QN) formula in which the Hess...
AbstractThis paper proposes a new robust and quickly convergent pattern search method based on an im...
AbstractIn this paper, we present a new symmetric rank-one (SR1) method for the solution of unconstr...