Akademik Veri Yönetim Sistemi
15th International Conference on Principles and Practice of Constraint Programming, CP 2009, Lisbon, Portekiz, 20 - 24 Eylül 2009, cilt.5732 LNCS, ss.684-691
Stochastic Constraint Programming is an extension of Constraint Programming for modelling and solving combinatorial problems involving uncertainty. A solution to such a problem is a policy tree that specifies decision variable assignments in each scenario. Several solution methods have been proposed but none seems practical for large multi-stage problems. We propose an incomplete approach: specifying a policy tree indirectly by a parameterised function, whose parameter values are found by evolutionary search. On some problems this method is orders of magnitude faster than a state-of-the-art scenario-based approach, and it also provides a very compact representation of policy trees. © 2009 Springer Berlin Heidelberg.