Multi-stage Stochastic Linear Programming: An Approach by Events

C. Beltran-Royo (cesar.beltranurjc.es)
L. F. Escudero (laureano.escuderourjc.es)
R. E. Rodriguez-Ravines (rerodriguezbayesforecast.com)

Abstract: To solve the multi-stage linear programming problem, one may use a deterministic or a stochastic approach. The drawbacks of the two techniques are well known: the deterministic approach is unrealistic under uncertainty and the stochastic approach suffers from scenario explosion. We introduce a new technique, whose objective is to overcome both drawbacks. The focus of this new technique is on events instead of scenarios and for this reason we call it Multi-stage Event Linear Programming (MELP). As we show in the theoretical results and in the preliminary computational experiments, the MELP approach represents a promising compromise between the stochastic and the deterministic approach, regarding capacity to deal with uncertainty and computational tractability.

Keywords: Multi-stage stochastic linear programming.

Category 1: Stochastic Programming

Citation: TR 2008/13. Rey Juan Carlos University, Mostoles (Madrid), Spain. July, 2008.

Download: [PDF]

Entry Submitted: 07/29/2008
Entry Accepted: 07/29/2008
Entry Last Modified: 07/29/2008

Modify/Update this entry