Abstract
Many combinatorial problems require of their solutions that they achieve a certain balance of given features. In the constraint programming literature, little has been written to specifically address this issue, particularly at the modeling level. We propose a new constraint dedicated to balancing, based on well-known and well-understood concepts in statistics. We show how it can be used to model different situations in which balance is important. We also design efficient filtering algorithms to guide the search towards balanced solutions.
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Pesant, G., Régin, JC. (2005). SPREAD: A Balancing Constraint Based on Statistics. In: van Beek, P. (eds) Principles and Practice of Constraint Programming - CP 2005. CP 2005. Lecture Notes in Computer Science, vol 3709. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564751_35
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DOI: https://doi.org/10.1007/11564751_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29238-8
Online ISBN: 978-3-540-32050-0
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