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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Using Constraint Programming for Solving Distance CSP with Uncertainty
verfasst von : Carlos Grandon, Bertrand Neveu
Erschienen in: Principles and Practice of Constraint Programming - CP 2005
Verlag: Springer Berlin Heidelberg
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Many problems in chemistry, robotics or molecular biology can be expressed as a Distance CSP (Constraint Satisfaction Problem). Sometimes, the parameters of this kind of problems are determined in an experimental way, and therefore they have an uncertainty degree. A classical approach for solving this class of problems is to solve the CSP without considering the uncertainties, and to obtain a set of solutions without knowing the real solution sub-spaces. A better approach is to apply a branch and prune algorithm to generate a set of disjoint boxes that include all the solution sub-spaces, but without information about independent solution sub-spaces or the different types of boxes.