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 <>
Soumis le : vendredi 24 octobre 2014 - 18:04:53 Dernière modification le : lundi 11 janvier 2021 - 17:24:14 Archivage à long terme le : : dimanche 25 janvier 2015 - 10:55:41