Abstract
Constraint satisfaction with numerical constraints is a fundamental problem in automated design. Traditional constraint satisfaction procedures are designed for problems where there is one constant set of constraints. In design, it is often necessary to solve a dynamic constraint satisfaction problem (DCSP) where the set of applicable constraints depends on design choices. Finding a solution in DCSP requires searching among different consistent sets of constraints to find one which has an acceptable numerical solution. In this paper, an algorithm is described which supports the propagation of numerical intervals in such a dynamic environment.KeywordsConstraint SatisfactionConstraint NetworkConstraint GraphDefault ReasoningPartial Order RelationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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