Incremental Filtering Algorithms for Precedence and Dependency Constraints
Roman Barták, Ondřej Čepek · Proceedings - International Conference on Tools with Artificial Intelligence, TAI · 2006
Precedence constraints play a crucial role in planning and scheduling problems. Many real-life problems also include dependency constraints expressing logical relations between the activities -- for example, an activity requires presence of another activity in the plan. For such problems a typical objective is a maximization of the number of activities satisfying the precedence and dependency constraints. In the paper we propose new incremental filtering rules integrating propagation through both precedence and dependency constraints. We also propose a new filtering rule using the information about the requested number of activities in the plan. We demonstrate efficiency of the proposed rules on the logbased reconciliation problems and min-cutset problems.