In this paper we present a framework for solving stochastic programs with complete integer recourse and discretely distributed right-hand side vector, using Gröbner basis methods from computational algebra to solve the numerous second-stage integer programs. Using structural properties of the expected integer recourse function, we prove that under mild conditions an optimal solution is contained in a finite set. Furthermore, we present a basic scheme to enumerate this set and suggest improvements to reduce the number of function evaluations needed
In this paper, we propose a new method to compute lower bounds on the optimal objective value of a s...
Stochastic optimization problems attempt to model uncertainty in the data by assuming that the input...
In this paper we present a solution method for stochastic integer problems. The method is a Benderst...
In this paper we present a framework for solving stochastic programs with complete integer recourse ...
In this paper we present a framework for solving stochastic programs with complete integer recourse ...
In this paper we present a framework for solving stochastic programs with complete integer recourse ...
In this paper we present a framework for solving stochastic programs with complete integer recourse ...
Stochastic integer programs are notoriously difficult. Very few properties are known and solution al...
We survey structural properties of and algorithms for stochastic integer programming models, mainly ...
We survey structural properties of and algorithms for stochastic integer programming models, mainly ...
In this thesis we consider two-stage stochastic linear programming models with integer recourse. Suc...
We consider two-stage pure integer programs with discretely distributed stochastic right-hand sides....
This paper addresses a general class of two-stage stochastic programs with integer recourse and disc...
In this paper we generalize N-fold integer programs and two-stage integer programs with N s...
In this paper, we propose a new method to compute lower bounds on the optimal objective value of a s...
Stochastic optimization problems attempt to model uncertainty in the data by assuming that the input...
In this paper we present a solution method for stochastic integer problems. The method is a Benderst...
In this paper we present a framework for solving stochastic programs with complete integer recourse ...
In this paper we present a framework for solving stochastic programs with complete integer recourse ...
In this paper we present a framework for solving stochastic programs with complete integer recourse ...
In this paper we present a framework for solving stochastic programs with complete integer recourse ...
Stochastic integer programs are notoriously difficult. Very few properties are known and solution al...
We survey structural properties of and algorithms for stochastic integer programming models, mainly ...
We survey structural properties of and algorithms for stochastic integer programming models, mainly ...
In this thesis we consider two-stage stochastic linear programming models with integer recourse. Suc...
We consider two-stage pure integer programs with discretely distributed stochastic right-hand sides....
This paper addresses a general class of two-stage stochastic programs with integer recourse and disc...
In this paper we generalize N-fold integer programs and two-stage integer programs with N s...
In this paper, we propose a new method to compute lower bounds on the optimal objective value of a s...
Stochastic optimization problems attempt to model uncertainty in the data by assuming that the input...
In this paper we present a solution method for stochastic integer problems. The method is a Benderst...