The intensive care unit (ICU) is one of the most crucial and expensive resources in a health care system. While high fixed costs usually lead to tight capacities, shortages have severe consequences. Thus, various challenging issues exist: When should an ICU admit or reject arriving patients in...

This paper offers several contributions to actual research and discussion on monetary policy. It clarifies the relationship between uncertainty of inflation persistence and optimal monetary policy and discusses the consequences of the recent Blanchard proposal to implement a higher inflation...

The paper deals with the analysis of a special dynamic production and inventory model. In this model logical restrictions to fulfill an accepted constant minimal level of the production lot size are incorporated, instead of keeping setup cost in the objective function, as it is common in many...

This paper continues the analysis of a special uncapacitated single item lot sizing problem where a minimum order quantity restriction, instead of the setup cost, guarantees a certain level of production lots. A detailed analysis of the model and an investigation of the particularities of the...

This paper explores a single-item capacitated lot sizing problem with minimum order quantity, which plays the role of minor set-up cost. We work out the necessary and suffcient solvability conditions and apply the general dynamic programming technique to develop an O(T³) exact algorithm that is...

We consider a model for a serial supply chain in which production, inventory, and transportation decisions are integrated, in the presence of production capacities and for different transportation cost functions. The model we study is a generalization of the traditional single-item economic...

In this paper we present a polynomial time dynamic programming algorithm for solving a scheduling problem with a (total) weighted completion time objective function where the weights are activity- and time-dependent. We highlight application areas for this type of problem to underscore the...

We propose a new methodology for structural estimation of dynamic discrete choice models. We combine the Dynamic Programming (DP) solution algorithm with the Bayesian Markov Chain Monte Carlo algorithm into a single algorithm that solves the DP problem and estimates the parameters...

We estimate a dynamic programming model of schooling decisions in which the degree of risk aversion can be inferred from schooling decisions. In our model, individuals are heterogeneous with respect to school and market abilities but homogeneous with respect to the degree of risk aversion. We...