The sample average approximation (SAA) method is an approach for solving stochastic optimization problems by using Monte Carlo simulation. The basic idea of such method is that we can approximate the expected objetive function by the corresponding sample average function using a random sample. We solve the obtained sample average approximating problem by deterministic optimization techniques, and the process is repeated several times with different samples to obtain candidate solutions along with statistical estimates of their optimality gaps until a stopping criterion is satisfied. In section 1 we describe the expected value and sample average approximation problems and give a few examples of real cases in which it can be useful. In secti...
Various stochastic programming problems can be formulated as problems of optimization of an expected...
Title: Sample approximation technique in stochastic programming Author: Eszter V¨or¨os Department: D...
In this paper we discuss the issue of solving stochastic optimization problems bymeans of sample ave...
The sample average approximation (SAA) method is an approach for solving stochastic optimization pr...
This thesis provides an overview of stochastic optimization (SP) problems and looks at how the Sampl...
We consider in this paper stochastic programming problems which can be formulated as an optimization...
We consider in this paper stochastic programming problems which can be formulated as an optimization...
Stochastic programming is a well-known instrument to model many risk management problems in finance....
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization p...
Abstract. Various stochastic programming problems can be formulated as problems of optimization of a...
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization p...
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization p...
The paper studies stochastic optimization (programming) problems with compound functions containing ...
Various stochastic programming problems can be formulated as problems of optimization of an expected...
Title: Sample approximation technique in stochastic programming Author: Eszter V¨or¨os Department: D...
Various stochastic programming problems can be formulated as problems of optimization of an expected...
Title: Sample approximation technique in stochastic programming Author: Eszter V¨or¨os Department: D...
In this paper we discuss the issue of solving stochastic optimization problems bymeans of sample ave...
The sample average approximation (SAA) method is an approach for solving stochastic optimization pr...
This thesis provides an overview of stochastic optimization (SP) problems and looks at how the Sampl...
We consider in this paper stochastic programming problems which can be formulated as an optimization...
We consider in this paper stochastic programming problems which can be formulated as an optimization...
Stochastic programming is a well-known instrument to model many risk management problems in finance....
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization p...
Abstract. Various stochastic programming problems can be formulated as problems of optimization of a...
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization p...
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization p...
The paper studies stochastic optimization (programming) problems with compound functions containing ...
Various stochastic programming problems can be formulated as problems of optimization of an expected...
Title: Sample approximation technique in stochastic programming Author: Eszter V¨or¨os Department: D...
Various stochastic programming problems can be formulated as problems of optimization of an expected...
Title: Sample approximation technique in stochastic programming Author: Eszter V¨or¨os Department: D...
In this paper we discuss the issue of solving stochastic optimization problems bymeans of sample ave...