The Bachelor thesis is dealing with Benders decomposition in optimization, especially in stochastic linear programming. In the begining the reader will be introduced to the important terms used in the decomposition algorithm. Con- sequently it is demonstrated how to reformulate the problem of stochastic linear programming to a special structure suitable for Benders decomposition. In the third chapter, the decomposition algorithm, using the feasibility and optimality cuts, is explained including conditions of convergence of the algorithm. There follows modification of algorithm for two stage stochastic linear programming. Finally, we illustrate Benders algorithm on two smaller problems.
We describe a generalization of Benders’ method for solving two-stage stochastic linear optimization...
summary:In this paper, we describe a decomposition algorithm suitable for two-stage convex stochasti...
This thesis offers methodological and computational contributions to several fields of operations re...
Benders decomposition is a solution method for solving certain large-scale optimization problems. In...
The thesis deals with the algorithms for two-stage stochastic programs. The first chapter considers ...
In a period when optimization has entered almost every facet of our lives, this thesis is designed t...
We consider two-stage stochastic programming problems with integer recourse. The L-shaped method of ...
Abstract. This document describes an implementation of Benders Decom-position for solving two-stage ...
This paper considers deterministic global optimization of scenario-based, two-stage stochastic mixed...
This paper introduces a new exact algorithm to solve two-stage stochastic linear programs. Based on ...
Dynamic multistage stochastic linear programming has many practical applications for problems whose ...
In this paper we present a heuristic approach to two-stage mixed-integer linear stochastic programmi...
In stochastic programming, the consideration of uncertainty might lead to large scale prob-lems. In ...
Stochastic linear programming problems are linear programming problems for which one or more data el...
Benders decomposition entails a two-stage optimization approach to a mixed integer program: first-s...
We describe a generalization of Benders’ method for solving two-stage stochastic linear optimization...
summary:In this paper, we describe a decomposition algorithm suitable for two-stage convex stochasti...
This thesis offers methodological and computational contributions to several fields of operations re...
Benders decomposition is a solution method for solving certain large-scale optimization problems. In...
The thesis deals with the algorithms for two-stage stochastic programs. The first chapter considers ...
In a period when optimization has entered almost every facet of our lives, this thesis is designed t...
We consider two-stage stochastic programming problems with integer recourse. The L-shaped method of ...
Abstract. This document describes an implementation of Benders Decom-position for solving two-stage ...
This paper considers deterministic global optimization of scenario-based, two-stage stochastic mixed...
This paper introduces a new exact algorithm to solve two-stage stochastic linear programs. Based on ...
Dynamic multistage stochastic linear programming has many practical applications for problems whose ...
In this paper we present a heuristic approach to two-stage mixed-integer linear stochastic programmi...
In stochastic programming, the consideration of uncertainty might lead to large scale prob-lems. In ...
Stochastic linear programming problems are linear programming problems for which one or more data el...
Benders decomposition entails a two-stage optimization approach to a mixed integer program: first-s...
We describe a generalization of Benders’ method for solving two-stage stochastic linear optimization...
summary:In this paper, we describe a decomposition algorithm suitable for two-stage convex stochasti...
This thesis offers methodological and computational contributions to several fields of operations re...