In this paper, a Stochastic Dynamic Facility Location Problem (SDFLP) is formulated. In the first part, an exact solution method based on stochastic dynamic programming is given. It is only usable for small instances. In the second part a Monte Carlo based method for solving larger instances is applied, which is derived from the Sample Average Approximation (SAA) method.

Stochastic programming is a well-known instrument to model many risk management problems in finance. In this paper we consider a stochastic programming model where the objective function is the variance of a random function and the constraint function is the expected value of the random function. Instead of using popular scenario tree methods, we apply the well-known sample average approximatio...

We study sample approximations of chance constrained problems. In particular, we consider the sample average approximation (SAA) approach and discuss the convergence properties of the resulting problem. We discuss how one can use the SAA method to obtain good candidate solutions for chance constrained ( )Departamento de Matemática, Pontif́ıcia Universidade Católica do Rio de Janeiro, Rio de Jane...

We deal with the problem of minimizing the expectation of a real valued random function over the weakly Pareto or Pareto set associated with a Stochastic MultiObjective Optimization Problem (SMOP) whose objectives are expectations of random functions. Assuming that the closed form of these expectations is difficult to obtain, we apply the Sample Average Approximation method (SAA-N, where N is t...

We consider constrained optimization problems with a nonsmooth objective function in the form of mathematical expectation. The Sample Average Approximation (SAA) is used to estimate and variable sample size strategy employed. proposed algorithm combines an SAA subgradient spectral coefficient order provide suitable direction which improves performance first method as shown by numerical results....

Elicitation of an exact utility function of a decision maker is challenging. In this paper, we address the problem of ambiguity and inconsistency in utility assessments by studying a robust utility-based decision making model where the utility function belongs to a set of general increasing utility functions. We build a robust framework in which the utility function belongs to a set. This set o...

This paper addresses the advance scheduling of elective surgeries in an operating theater composed rooms and a downstream surgical intensive care unit (SICU). The arrivals new patients each week, duration surgery, length-of-stay patient SICU are subject to uncertainty. At end surgery planner determines blocks open next week assigns subset on waiting list blocks. objective is minimize patient-re...

The sample average approximation (SAA) method is a basic approach for solving stochastic variational inequalities (SVI). It is well known that under appropriate conditions the SAA solutions provide asymptotically consistent point estimators for the true solution to an SVI. It is of fundamental interest to use such point estimators along with suitable central limit results to develop confidence ...

The sample average approximation (SAA) approach is a widely used technique, based on MonteCarlo simulation, often applied to large-scale stochastic optimization problems. In this approach, a set of sample average problems with multiple copies of sampled scenarios are generated and solved exactly. In other words, there is an implicit assumption that the sample average problems are solvable to op...

It remains unclear how salivary alpha-amylase (sAA) levels respond to mechanical stimuli in different age groups. In addition, the role played by the sAA gene (AMY1) copy number and protein expression (glycosylated and non-glycosylated) in sAA activity has also been rarely reported. In this study, we analyzed saliva samples collected before and after citric acid stimulation from 47 child and 47...