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The Ubiquity Generator Framework: 7 Years of Progress in Parallelizing Branch-and-Bound

In: Operations Research Proceedings 2017

Author

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  • Yuji Shinano

    (Zuse Institute Berlin)

Abstract

Mixed integer linear programming (MILP) is a general form to model combinatorial optimization problems and has many industrial applications. The performance of MILP solvers has improved tremendously in the last two decades and these solvers have been used to solve many real-word problems. However, against the backdrop of modern computer technology, parallelization is of pivotal importance. In this way, ParaSCIP is the most successful parallel MILP solver in terms of solving previously unsolvable instances from the well-known benchmark instance set MIPLIB by using supercomputers. It solved two instances from MIPLIB2003 and 12 from MIPLIB2010 for the first time to optimality by using up to 80,000 cores on supercomputers. ParaSCIP has been developed by using the Ubiquity Generator (UG) framework, which is a general software package to parallelize any state-of-the-art branch-and-bound based solver. This paper discusses 7 years of progress in parallelizing branch-and-bound solvers with UG.

Suggested Citation

  • Yuji Shinano, 2018. "The Ubiquity Generator Framework: 7 Years of Progress in Parallelizing Branch-and-Bound," Operations Research Proceedings, in: Natalia Kliewer & Jan Fabian Ehmke & Ralf Borndörfer (ed.), Operations Research Proceedings 2017, pages 143-149, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-89920-6_20
    DOI: 10.1007/978-3-319-89920-6_20
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    Cited by:

    1. Meenarli Sharma & Prashant Palkar & Ashutosh Mahajan, 2022. "Linearization and parallelization schemes for convex mixed-integer nonlinear optimization," Computational Optimization and Applications, Springer, vol. 81(2), pages 423-478, March.

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