Solving a set of global optimization problems by the parallel technique with uniform convergence

Konstantin Barkalov () and Roman Strongin ()
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Konstantin Barkalov: Lobachevsky State University of Nizhni Novgorod
Roman Strongin: Lobachevsky State University of Nizhni Novgorod

Journal of Global Optimization, 2018, vol. 71, issue 1, No 3, 36 pages

Abstract: Abstract In this paper, we consider solving a set of global optimization problems in parallel. The proposed novel algorithm provides uniform convergence to the set of solutions for all problems treated simultaneously. The current accuracy for each particular solution is estimated by the difference in each coordinate from the point of global decision. The main statement is given in the corresponding theorem. For the sake of illustration some computational results with hundreds of multidimensional global problems are provided.

Keywords: Global optimization; Peano-type space filling curves; Uniform convergence; Parallel computing (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s10898-017-0555-4

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