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Combining Local Search and Constraint Propagation to Find a Minimal Change Solution for a Dynamic CSP Export

In Artificial Intelligence: Methodology, Systems, Applications (2000), pp. 272-282.

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Many hard practical problems such as Time Tabling and Scheduling can be formulated as Constraint Satisfaction Problems. For these CSPs, powerful problem-solving methods are available. However, in practice, the problem definition may change over time. Each separate change may invoke a new CSP formulation. The resulting sequence of CSPs is denoted as a Dynamic CSP.


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