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    Stochastic Constraint Programming: A Scenario-Based Approach

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    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 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.

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    Description

    Title : Stochastic Constraint Programming: A Scenario-Based Approach
    Author(s) : S. Armagan Tarim, Suresh Manandhar, Toby Walsh
    Abstract : 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 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.
    Keywords : constraint programming, constraint satisfaction, reasoning under uncertainty

    Subject : unspecified
    Area : Other
    Language : English
    Year : 2009

    Affiliations NICTA and UNSW
    Journal : Constraints
    Volume : 11
    Issue : 1
    Publisher : Springer
    Pages : 53 - 80
    Url : http://www.springerlink.com/index/10.1007/s10601-006-6849-7
    Doi : 10.1007/s10601-006-6849-7

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    Toby's Peer Evaluation activity

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    Title of the work: HP90: A general & flexible Fortran 90 hp-FE code

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