Clairvoyant Restarts in Branch-and-Bound Search Using Online Tree-Size Estimation

accepted for publication
  • We propose a simple and general online method to measure the search progress within the branch-and-bound algorithm, from which we estimate the size of the remaining search tree. We then show how this information can help solvers algorithmically at runtime by designing a restart strategy for Mixed-Integer Programming (MIP) solvers that decides whether to restart the search based on the current estimate of the number of remaining nodes in the tree. We refer to this type of algorithm as clairvoyant. Our clairvoyant restart strategy outperforms a state-of-the-art solver on a large set of publicly available MIP benchmark instances. It is implemented in the MIP solver SCIP and will be available in future releases.
Metadaten
Author:Daniel Anderson, Gregor HendelORCiD, Pierre Le Bodic, Jan Merlin Viernickel
Document Type:In Proceedings
Parent Title (German):AAAI-19: Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence
Year of first publication:2018
Preprint:urn:nbn:de:0297-zib-72653