Stochastic constraint programming: A scenario-based approach

TARIM Ş. A., Manandhar S., Walsh T.

Constraints, cilt.11, sa.1, ss.53-80, 2006 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 11 Sayı: 1
  • Basım Tarihi: 2006
  • Doi Numarası: 10.1007/s10601-006-6849-7
  • Dergi Adı: Constraints
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.53-80
  • Anahtar Kelimeler: Constraint programming, Constraint satisfaction, Reasoning under uncertainty
  • Hacettepe Üniversitesi Adresli: Evet

Özet

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. © Springer Science + Business Media, LLC 2006.