Journal of Global Optimization

, Volume 64, Issue 2, pp 289–304 | Cite as

Node selection strategies in interval Branch and Bound algorithms

  • Bertrand Neveu
  • Gilles TrombettoniEmail author
  • Ignacio Araya


We present in this article new strategies for selecting nodes in interval Branch and Bound algorithms for constrained global optimization. For a minimization problem the standard best-first strategy selects a node with the smallest lower bound of the objective function estimate. We first propose 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 contracting operators leads to a good performance of the node selection rule based on this criterion. We propose another strategy that also makes a tradeoff between diversification and intensification by greedily diving into potential feasible regions at each node of the best-first search. These new strategies obtain better experimental results than classical best-first search on difficult constrained global optimization instances.


Intervals Global optimization Node selection  Branch and Bound 


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Bertrand Neveu
    • 1
  • Gilles Trombettoni
    • 2
    Email author
  • Ignacio Araya
    • 3
  1. 1.Imagine LIGM Université Paris–EstParisFrance
  2. 2.LIRMM, CNRSUniversity of MontpellierMontpellierFrance
  3. 3.Pontificia Universidad Católica de ValparaísoValparaisoChile

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