We give a bundle method for minimizing the sum of two convex functions, one of them being known only via an oracle of arbitrary accuracy. Each iteration involves solving two subproblems in which the functions are alternately represented by their linearizations. Our approach is motivated by applications to nonlinear multicommodity flow problems. Encouraging numerical experience on large scale problems is reported
For three rather diverse applications (truck scheduling for inter warehouse logistics, university-co...
The author considers the problem of minimizing a convex function of two variables without computing ...
In this paper, we propose a logarithmic-quadratic proximal alternating direction method for structur...
We give a bundle method for minimizing the sum of two convex functions, one of them being known only...
We propose a family of proximal bundle methods for minimizing sum-structured convex nondifferentiabl...
A new approximate proximal point method for minimizing the sum of two convex functions is introduced...
International audienceWe consider convex nonsmooth optimization problems where additional informatio...
We review the basic ideas underlying the vast family of algorithms for nonsmooth convex optimization...
Abstract In this paper, we propose an alternating linearization bundle method for minimizing the sum...
Final version to appear in Mathematical Programming Available in www.springerlink.com DOI 10.1007/s1...
We give a bundle method for minimizing a (possibly nondifferentiable and nonconvex) function h(z) = ...
We propose a modification to the (generalized) bundle scheme for minimization of a convex nondiffere...
We propose a version of the bundle scheme for convex nondifferentiable optimization suitable for the...
We present a new inexact nonsmooth Newton method for the solution of convex minimization problems wi...
We propose a version of the (generalized) bundle scheme for convex nondifferentiable optimization su...
For three rather diverse applications (truck scheduling for inter warehouse logistics, university-co...
The author considers the problem of minimizing a convex function of two variables without computing ...
In this paper, we propose a logarithmic-quadratic proximal alternating direction method for structur...
We give a bundle method for minimizing the sum of two convex functions, one of them being known only...
We propose a family of proximal bundle methods for minimizing sum-structured convex nondifferentiabl...
A new approximate proximal point method for minimizing the sum of two convex functions is introduced...
International audienceWe consider convex nonsmooth optimization problems where additional informatio...
We review the basic ideas underlying the vast family of algorithms for nonsmooth convex optimization...
Abstract In this paper, we propose an alternating linearization bundle method for minimizing the sum...
Final version to appear in Mathematical Programming Available in www.springerlink.com DOI 10.1007/s1...
We give a bundle method for minimizing a (possibly nondifferentiable and nonconvex) function h(z) = ...
We propose a modification to the (generalized) bundle scheme for minimization of a convex nondiffere...
We propose a version of the bundle scheme for convex nondifferentiable optimization suitable for the...
We present a new inexact nonsmooth Newton method for the solution of convex minimization problems wi...
We propose a version of the (generalized) bundle scheme for convex nondifferentiable optimization su...
For three rather diverse applications (truck scheduling for inter warehouse logistics, university-co...
The author considers the problem of minimizing a convex function of two variables without computing ...
In this paper, we propose a logarithmic-quadratic proximal alternating direction method for structur...