Abstract
This paper presents a sweep based algorithm for the k-dimensional cumulative constraint, which can operate in filtering mode as well as in greedy assignment mode. Given n tasks and k resources, this algorithm has a worst-case time complexity of O(kn 2) but scales well in practice. In greedy assignment mode, it handles up to 1 million tasks with 64 resources in one single constraint in SICStus. In filtering mode, on our benchmarks, it yields a speed-up of about k 0.75 when compared to its decomposition into k independent cumulative constraints.
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Letort, A., Carlsson, M., Beldiceanu, N. (2013). A Synchronized Sweep Algorithm for the k-dimensional cumulative Constraint. In: Gomes, C., Sellmann, M. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2013. Lecture Notes in Computer Science, vol 7874. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38171-3_10
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DOI: https://doi.org/10.1007/978-3-642-38171-3_10
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