Add to ORKGIn a recent paper, V.F. Demyanov, S. Gamidov and I. Sivelina developed an algorithm for solving optimization problems, given by smooth compositions of max-type functions. In this paper the authors apply this algorithm to a larger class of quasidifferentiable functions. This paper is a contribution to research on nondifferentiable optimization currently underway with the System and Decision Sciences Program
The steepest descent method has a rich history and is one of the simplest and best known methods for...
This thesis is concerned with analyzing and improving the performance of quasi-Newton methods for f...
Some results concerning second order expansions for quasidifferentiable functions in the sense of De...
In this paper the author studies the necessary conditions for an extremum when either the function t...
To minimize a continuously differentiable quasiconvex function f : ℝ n →ℝ, Armijo's steepest descent...
This paper presents a survey of results related to quasidifferential calculus. First we discuss diff...
The article is dedicated of memory of Professor V. F. Demyanov (1938—2014). The main scientific int...
This paper considers the problem of minimizing a quasidifferentiable function on a set described by ...
Much recent work in optimization theory has been concerned with the problems caused by nondifferenti...
Kiwiel and Murty (1996) discuss the convergence properties of a class of steepest descent algorithm ...
In this paper a new algorithm for minimizing locally Lipschitz functions is developed. Descent direc...
For the minimization of nonsmooth quasidifferentiable functions methods have been defined which make...
AbstractIn this work we propose a Cauchy-like method for solving smooth unconstrained vector optimiz...
The success of Newton’s method for smooth optimization, when Hessians are available, motivated the i...
In this paper, we propose a new method for the unconstrained minimization of a function presented as...
The steepest descent method has a rich history and is one of the simplest and best known methods for...
This thesis is concerned with analyzing and improving the performance of quasi-Newton methods for f...
Some results concerning second order expansions for quasidifferentiable functions in the sense of De...
In this paper the author studies the necessary conditions for an extremum when either the function t...
To minimize a continuously differentiable quasiconvex function f : ℝ n →ℝ, Armijo's steepest descent...
This paper presents a survey of results related to quasidifferential calculus. First we discuss diff...
The article is dedicated of memory of Professor V. F. Demyanov (1938—2014). The main scientific int...
This paper considers the problem of minimizing a quasidifferentiable function on a set described by ...
Much recent work in optimization theory has been concerned with the problems caused by nondifferenti...
Kiwiel and Murty (1996) discuss the convergence properties of a class of steepest descent algorithm ...
In this paper a new algorithm for minimizing locally Lipschitz functions is developed. Descent direc...
For the minimization of nonsmooth quasidifferentiable functions methods have been defined which make...
AbstractIn this work we propose a Cauchy-like method for solving smooth unconstrained vector optimiz...
The success of Newton’s method for smooth optimization, when Hessians are available, motivated the i...
In this paper, we propose a new method for the unconstrained minimization of a function presented as...
The steepest descent method has a rich history and is one of the simplest and best known methods for...
This thesis is concerned with analyzing and improving the performance of quasi-Newton methods for f...
Some results concerning second order expansions for quasidifferentiable functions in the sense of De...