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Parallel Branch and Bound Algorithm with Combination of Lipschitz Bounds over Multidimensional Simplices for Multicore Computers

In: Parallel Scientific Computing and Optimization

Author

Listed:
  • Remigijus Paulavičius

    (Vilnius Pedagogical University)

  • Julius Žilinskas

    (Vilnius Gediminas Technical University)

Abstract

Parallel branch and bound for global Lipschitz minimization is considered. A combination of extreme (infinite and first) and Euclidean norms over a multidimensional simplex is used to evaluate the lower bound. OpenMP has been used to implement the parallel version of the algorithm for multicore computers. The efficiency of the developed parallel algorithm is investigated solving multidimensional test functions for global optimization.

Suggested Citation

  • Remigijus Paulavičius & Julius Žilinskas, 2009. "Parallel Branch and Bound Algorithm with Combination of Lipschitz Bounds over Multidimensional Simplices for Multicore Computers," Springer Optimization and Its Applications, in: Parallel Scientific Computing and Optimization, pages 93-102, Springer.
    • Handle: RePEc:spr:spochp:978-0-387-09707-7_8
    DOI: 10.1007/978-0-387-09707-7_8
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    Citations

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    Cited by:

    1. Stripinis, Linas & Žilinskas, Julius & Casado, Leocadio G. & Paulavičius, Remigijus, 2021. "On MATLAB experience in accelerating DIRECT-GLce algorithm for constrained global optimization through dynamic data structures and parallelization," Applied Mathematics and Computation, Elsevier, vol. 390(C).
    2. Schryen, Guido, 2020. "Parallel computational optimization in operations research: A new integrative framework, literature review and research directions," European Journal of Operational Research, Elsevier, vol. 287(1), pages 1-18.

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