2002 | OriginalPaper | Buchkapitel
On Constraint Problems with Incomplete or Erroneous Data
verfasst von : Neil Yorke-Smith
Erschienen in: Principles and Practice of Constraint Programming - CP 2002
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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Real-world Large Scale Combinatorial Optimisation problems (LSCOs) have inherent data uncertainties. The uncertainty can be due to the dynamic and unpredictable nature of the commercial world, but also due to the information available to those modelling the problem. We are concerned with the latter form of uncertainty, which can arise when the data is not fully known or is even erroneous. Our work is motivated by practical issues faced in real-world applications, for instance in energy trading [1]. Here, the demand and cost profiles have evolved due to market privatisation; thus the existing simulation or stochastic data models would not help address the actual problem.