We give multi-stage stochastic programming formulations for lot-sizing problems where costs, demands and order lead times follow a general discrete-time stochastic process with finite support. We characterize the properties of an optimal solution and give a dynamic programming algorithm, polynomial in input size, when orders do not cross in time.

This short paper introduces the concept of Asian options in the capacity choice literature. We develop a simple model for optimal capacity setting under average demand uncertainty for a single firm. When the firm faces moderate or significant stochastic demands in its current product line, expanding capacity is beneficial. If the demand is extremely stochastic, a capacity lag or reduction is mo...

We present a new algorithm that uses both local branching and Monte Carlo sampling in a multi-descent search strategy for solving 0-1 integer stochastic programming problems. This procedure is applied to the single vehicle routing problem with stochastic demands. Computational results show the usefulness of this new approach to solve hard instances of the problem.

The unit commitment problem is to find the production scheduling of a set of electric power generating units, and the generation levels for each unit, over a short term, typically from 24 hours to one week. The objective is to find the optimal schedule which meets the energy demand forecast at a minimum cost, and satisfy technological constraints such as the minimum up and down times for the un...