Energetic reasoning is one of the most powerful propagation algorithms in cumulative scheduling. In practice, however, it is not commonly used because it has a high running time and its success highly depends on the tightness of the variable bounds. In order to speed up energetic reasoning, we provide an easy-to-check necessary condition for energetic reasoning to detect infeasibilities. We present an implementation of energetic reasoning that employs this condition and that can be parametrically adjusted to handle the trade-off between solving time and propagation overhead. Computational results on instances from the PSPLib are provided. These results show that using this condition decreases the running time by more than a half, although more search nodes need to be explored. © 2011 Springer-Verlag.
CITATION STYLE
Berthold, T., Heinz, S., & Schulz, J. (2011). An approximative criterion for the potential of energetic reasoning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6595 LNCS, pp. 229–239). https://doi.org/10.1007/978-3-642-19754-3_23
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