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CP
2008
Springer

Cost-Based Domain Filtering for Stochastic Constraint Programming

14 years 29 days ago
Cost-Based Domain Filtering for Stochastic Constraint Programming
Abstract. Cost-based filtering is a novel approach that combines techniques from Operations Research and Constraint Programming to filter from decision variable domains values that do not lead to better solutions [7]. Stochastic Constraint Programming is a framework for modeling combinatorial optimization problems that involve uncertainty [19]. In this work, we show how to perform cost-based filtering for certain classes of stochastic constraint programs. Our approach is based on a set of known inequalities borrowed from Stochastic Programming -- a branch of OR concerned with modeling and solving problems involving uncertainty. We discuss bound generation and cost-based domain filtering procedures for a well-known problem in the Stochastic Programming literature, the static stochastic knapsack problem. We also apply our technique to a stochastic sequencing problem. Our results clearly show the value of the proposed approach over a pure scenario-based Stochastic Constraint Programming f...
Roberto Rossi, Armagan Tarim, Brahim Hnich, Steven
Added 18 Oct 2010
Updated 18 Oct 2010
Type Conference
Year 2008
Where CP
Authors Roberto Rossi, Armagan Tarim, Brahim Hnich, Steven David Prestwich
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