Synchronized sweep algorithms for scalable scheduling constraints

This paper introduces a family of synchronized sweep-based filtering algorithms for handling scheduling problems involving resource and precedence constraints. The key idea is to filter all constraints of a scheduling problem in a synchronized way in order to scale better. In addition to normal filtering mode, the algorithms can run in greedy mode, in which case they perform a greedy assignment of start and end times. The filtering mode achieves a significant speed-up over the decomposition into independent cumulative and precedence constraints, while the greedy mode can handle up to 1 million tasks with 64 resource constraints and 2 million precedences. These algorithms were implemented in both CHOCO and SICStus.

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