We consider two-stage stochastic programming problems with integer recourse. The L-shaped method of stochastic linear programming is generalized to these problems by using generalized Benders decomposition. Nonlinear feasibility and optimality cuts are determined via general duality theory and can be generated when the second stage problem is solved by standard techniques. Finite convergence of the method is established when Gomory's fractional cutting plane algorithm or a branch-and-bound algorithm is applied.
http://deepblue.lib.umich.edu/bitstream/2027.42/3628/5/bbm0214.0001.001.pdfhttp://deepblue.lib.umich...
In this paper, we study recourse-based stochastic nonlinear programs and make two sets of contributi...
Abstract We describe a decomposition algorithm that combines Benders and scenario-based Lagrangean d...
We consider two-stage stochastic programming problems with integer recourse. The L-shaped method of ...
We consider the integer L-shaped method for two-stage stochastic integer programs. To improve the pe...
We describe a generalization of Benders’ method for solving two-stage stochastic linear optimization...
This paper focuses on solving two-stage stochastic mixed integer programs (SMIPs) with general mixed...
The thesis deals with the algorithms for two-stage stochastic programs. The first chapter considers ...
We introduce the two-stage stochastic minimum s − t cut problem. Based on a classical linear 0-1 pro...
Stochastic programming problems have very large dimension and characteristic structures which are tr...
Stochastic linear programming problems are linear programming problems for which one or more data el...
Benders decomposition is one of the most applied methods to solve two-stage stochastic problems (TSS...
We introduce the two‐stage stochastic minimum s − t cut problem. Based on a classical linear 0‐1 pro...
The Bachelor thesis is dealing with Benders decomposition in optimization, especially in stochastic ...
This paper introduces a new exact algorithm to solve two-stage stochastic linear programs. Based on ...
http://deepblue.lib.umich.edu/bitstream/2027.42/3628/5/bbm0214.0001.001.pdfhttp://deepblue.lib.umich...
In this paper, we study recourse-based stochastic nonlinear programs and make two sets of contributi...
Abstract We describe a decomposition algorithm that combines Benders and scenario-based Lagrangean d...
We consider two-stage stochastic programming problems with integer recourse. The L-shaped method of ...
We consider the integer L-shaped method for two-stage stochastic integer programs. To improve the pe...
We describe a generalization of Benders’ method for solving two-stage stochastic linear optimization...
This paper focuses on solving two-stage stochastic mixed integer programs (SMIPs) with general mixed...
The thesis deals with the algorithms for two-stage stochastic programs. The first chapter considers ...
We introduce the two-stage stochastic minimum s − t cut problem. Based on a classical linear 0-1 pro...
Stochastic programming problems have very large dimension and characteristic structures which are tr...
Stochastic linear programming problems are linear programming problems for which one or more data el...
Benders decomposition is one of the most applied methods to solve two-stage stochastic problems (TSS...
We introduce the two‐stage stochastic minimum s − t cut problem. Based on a classical linear 0‐1 pro...
The Bachelor thesis is dealing with Benders decomposition in optimization, especially in stochastic ...
This paper introduces a new exact algorithm to solve two-stage stochastic linear programs. Based on ...
http://deepblue.lib.umich.edu/bitstream/2027.42/3628/5/bbm0214.0001.001.pdfhttp://deepblue.lib.umich...
In this paper, we study recourse-based stochastic nonlinear programs and make two sets of contributi...
Abstract We describe a decomposition algorithm that combines Benders and scenario-based Lagrangean d...