Abstract : We present in this article a new strategy for selecting the current node in an interval Branch and Bound algorithm for constrained global optimization. The standard best-first strategy selects the node with the lowest lower bound of the objective estimate. We propose in this article new node selection policies where an upper bound of each node/box is also taken into account. The good accuracy of this upper bound achieved by several operators leads to a good performance of the criterion. These new strategies obtain better experimental results than classical best-first search on difficult instances.
https://hal-enpc.archives-ouvertes.fr/hal-01077483
Contributeur : Bertrand Neveu
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Soumis le : vendredi 24 octobre 2014 - 18:04:53
Dernière modification le : jeudi 26 juillet 2018 - 12:16:02
Document(s) archivé(s) le : dimanche 25 janvier 2015 - 10:55:41
