We present an integrated framework able to handle both quantitative and qualitative constraints affected by vagueness and uncertainty. We merge two existing models: the Meiri’s system [Meiri, 1996] and IA [Badaloni and Giacomin, 2000a; 2000b]; the first approach is generalized with possi- bility theory, while the second is extended in order to include qualitative constraints. Two traditional solving techniques such as Path-Consistency and Branch and Bound are taken into account. A simple scheduling example shows the main features of the new system.
Integrating Qualitative and Quantative Constraints in Fuzzy Temporal Networks
BADALONI, SILVANA;FALDA, MARCO;
2003
Abstract
We present an integrated framework able to handle both quantitative and qualitative constraints affected by vagueness and uncertainty. We merge two existing models: the Meiri’s system [Meiri, 1996] and IA [Badaloni and Giacomin, 2000a; 2000b]; the first approach is generalized with possi- bility theory, while the second is extended in order to include qualitative constraints. Two traditional solving techniques such as Path-Consistency and Branch and Bound are taken into account. A simple scheduling example shows the main features of the new system.
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