Policy makers constantly face optimal control problems: what controls allow to achieve certain targets in, e.g., GDP growth or inflation? Conventionally this is done by applying certain linear- quadratic optimization algorithms to dynamic econometric models. Several algorithms extend this...

A number of optimal decision problems with uncertainty can be formulated into a stochastic optimal control framework. The Least-Squares Monte Carlo (LSMC) algorithm is a popular numerical method to approach solutions of such stochastic control problems as analytical solutions are not tractable...

In this paper, we consider a company that can satisfy customers' demands for a product using two alternative sourcing strategies: (1) purchasing new products from outside sources (such as an international partner) or (2) collecting cores (used products) and remanufacturing them. As the purchase...

Policy makers constantly face optimal control problems: what controls allow to achieve certain targets in, e.g., GDP growth or inflation? Conventionally this is done by applying certain linear-quadratic optimization algorithms to dynamic econometric models. Several algorithms extend this...