Tarim, S.A., Manandhar, S. and Walsh, T. (2006) Stochastic constraint programming: A scenario based approach. Journal of Constraints, 11 (1). pp. 53-80. ISSN 1383-7133Full text not available from this repository.
To model combinatorial decision problems involving uncertainty and probability, we introduce scenario based stochastic constraint programming. Stochastic constraint programs contain both decision variables, which we can set, and stochastic variables, which follow a discrete probability distribution. We provide a semantics for stochastic constraint programs based on scenario trees. Using this semantics, we can compile stochastic constraint programs down into conventional (non-stochastic) constraint programs. This allows us to exploit the full power of existing constraint solvers. We have implemented this framework for decision making under uncertainty in stochastic OPL, a language which is based on the OPL constraint modelling language [Van Hentenryck et al., 1999]. To illustrate the potential of this framework, we model a wide range of problems in areas as diverse as portfolio diversification, agricultural planning and production/inventory management.
|Institution:||The University of York|
|Academic Units:||The University of York > Computer Science (York)|
|Depositing User:||York RAE Import|
|Date Deposited:||23 Apr 2009 15:34|
|Last Modified:||23 Apr 2009 15:34|
|Publisher:||Springer Verlag (Germany)|