Parallel Hybrid Best-First Search

Authors Abdelkader Beldjilali, Pierre Montalbano , David Allouche, George Katsirelos , Simon de Givry

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Abdelkader Beldjilali
  • Université Fédérale de Toulouse, INRAE, UR 875, 31326 Toulouse, France
Pierre Montalbano
  • Université Fédérale de Toulouse, ANITI, INRAE, UR 875, 31326 Toulouse, France
David Allouche
  • Université Fédérale de Toulouse, ANITI, INRAE, UR 875, 31326 Toulouse, France
George Katsirelos
  • Université Fédérale de Toulouse, ANITI, INRAE, MIA Paris, AgroParisTech, 75231 Paris, France
Simon de Givry
  • Université Fédérale de Toulouse, ANITI, INRAE, UR 875, 31326 Toulouse, France

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Abdelkader Beldjilali, Pierre Montalbano, David Allouche, George Katsirelos, and Simon de Givry. Parallel Hybrid Best-First Search. In 28th International Conference on Principles and Practice of Constraint Programming (CP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 235, pp. 7:1-7:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


While processor frequency has stagnated over the past two decades, the number of available cores in servers or clusters is still growing, offering the opportunity for significant speed-up in combinatorial optimization. Parallelization of exact methods remains a difficult challenge. We revisit the concept of parallel Branch-and-Bound in the framework of Cost Function Networks. We show how to adapt the anytime Hybrid Best-First Search algorithm in a Master-Worker protocol. The resulting parallel algorithm achieves good load-balancing without introducing new parameters to be tuned as is the case, for example, in Embarrassingly Parallel Search (EPS). It has also a small overhead due to its light communication messages. We performed an experimental evaluation on several benchmarks, comparing our parallel algorithm to its sequential version. We observed linear speed-up in some cases. Our approach compared favourably to the EPS approach and also to a state-of-the-art parallel exact integer programming solver.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Parallel algorithms
  • Combinatorial Optimization
  • Parallel Branch-and-Bound
  • CFN


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