Abstract
We study a global constraint, the "inter-distance constraint" that ensures that the distance between any pair of variables is at least equal to a given value. When this value is 1, the inter-distance constraint reduces to the all-different constraint. We introduce an algorithm to propagate this constraint and we show that, when domains of the variables are intervals, our algorithm achieves arc-B-consistency. It provides tighter bounds than generic scheduling constraint propagation algorithms (like edge-finding) that could be used to capture this constraint. The worst case complexity of the algorithm is cubic but it behaves well in practice and it drastically reduces the search space. Experiments on special Job-Shop problems and on an industrial problem are reported. © Springer-Verlag Berlin Heidelberg 2005.
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CITATION STYLE
Artiouchine, K., & Baptiste, P. (2005). Inter-distance constraint: An extension of the all-different constraint for scheduling equal length jobs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3709 LNCS, pp. 62–76). https://doi.org/10.1007/11564751_8
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