Recently two new ways of obtaining improved Lagrangean bounds have been suggested: Variable splitting/ Lagrangean decomposition and bound improving sequences. The aim of this work is to obtain a Lagrangean approach combining the two ideas mentioned above. We provide some theoretical results about the sharpness of the bounds obtained by the combined approach. We show that they dominate the bounds obtained by any of the two individual techniques.N/
International audienceLagrangian relaxation is usually considered in the combinatorial optimization ...
Lagrangian relaxation is a widely used decomposition approach to solve difficult optimization proble...
AbstractThe aim of this paper is to point out some sufficient constraint qualification conditions en...
Recently two new ways of obtaining improved Lagrangean bounds have been suggested: Variable splittin...
Recently two new ways of obtaining improved Lagrangean bounds have been suggested: Lagrangean decomp...
In this thesis we propose a novel way to use subgradients and the Lagrangean multipliers to construc...
International audienceWe propose in this paper a new Dantzig-Wolfe master model based on Lagrangian ...
Lagrangian relaxation is commonly used in combinatorial optimization to generate lower bounds for a ...
Operations in areas of importance to society are frequently modeled as Mixed-Integer Linear Programm...
AbstractIn this paper, a new Lagrangian function is reported which is particularly suited for large-...
Classical and modified Lagrangian bounds for the optimal value of optimization problems with a doubl...
Subgradient methods (SM) have long been the preferred way to solve the large-scale Nondifferentiable...
It is well-known that the Lagrangian dual of an Integer Linear Program (ILP) provides the same bound...
International audienceThis article presents a family of semidefinite programming bounds, obtained by...
We propose a general dual ascent framework for Lagrangean decomposition of combinatorial pro...
International audienceLagrangian relaxation is usually considered in the combinatorial optimization ...
Lagrangian relaxation is a widely used decomposition approach to solve difficult optimization proble...
AbstractThe aim of this paper is to point out some sufficient constraint qualification conditions en...
Recently two new ways of obtaining improved Lagrangean bounds have been suggested: Variable splittin...
Recently two new ways of obtaining improved Lagrangean bounds have been suggested: Lagrangean decomp...
In this thesis we propose a novel way to use subgradients and the Lagrangean multipliers to construc...
International audienceWe propose in this paper a new Dantzig-Wolfe master model based on Lagrangian ...
Lagrangian relaxation is commonly used in combinatorial optimization to generate lower bounds for a ...
Operations in areas of importance to society are frequently modeled as Mixed-Integer Linear Programm...
AbstractIn this paper, a new Lagrangian function is reported which is particularly suited for large-...
Classical and modified Lagrangian bounds for the optimal value of optimization problems with a doubl...
Subgradient methods (SM) have long been the preferred way to solve the large-scale Nondifferentiable...
It is well-known that the Lagrangian dual of an Integer Linear Program (ILP) provides the same bound...
International audienceThis article presents a family of semidefinite programming bounds, obtained by...
We propose a general dual ascent framework for Lagrangean decomposition of combinatorial pro...
International audienceLagrangian relaxation is usually considered in the combinatorial optimization ...
Lagrangian relaxation is a widely used decomposition approach to solve difficult optimization proble...
AbstractThe aim of this paper is to point out some sufficient constraint qualification conditions en...