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.
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Paulavičius, R., Žilinskas, J. (2009). Parallel Branch and Bound Algorithm with Combination of Lipschitz Bounds over Multidimensional Simplices for Multicore Computers. In: Parallel Scientific Computing and Optimization. Springer Optimization and Its Applications, vol 27. Springer, New York, NY. https://doi.org/10.1007/978-0-387-09707-7_8
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DOI: https://doi.org/10.1007/978-0-387-09707-7_8
Publisher Name: Springer, New York, NY
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