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Combining Local and Global Search in a Parallel Nested Optimization Scheme

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Parallel Computational Technologies (PCT 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1263))

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Abstract

This paper considers global optimization problems and numerical methods to solve them. The following assumption is made regarding the dependence of the objective function on its parameters: it is multiextremal concerning selected variables only, and the dependence on the other variables has a local character. Such problems may arise when identifying unknown parameters of the mathematical models based on experimental results. A parallel computational scheme, which accounts for this feature, is being proposed. This novel scheme is based on the idea of nested (recursive) optimization, which suggests optimizing the significant variables at the upper recursion level (using the global optimization method) and solving the local optimization problems at the lower level (using the local method). The generated local subproblems will not affect each other and can be solved in parallel. The efficiency of the proposed parallel computation scheme has been confirmed by the numerical experiments conducted on several hundreds of test problems.

This study was supported by the Russian Science Foundation, project No. 16-11-10150.

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Authors and Affiliations

  1. Lobachevsky State University of Nizhni Novgorod, Nizhni Novgorod, Russia

    Konstantin Barkalov, Ilya Lebedev, Maria Kocheganova & Victor Gergel

Authors
  1. Konstantin Barkalov
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  2. Ilya Lebedev
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  3. Maria Kocheganova
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  4. Victor Gergel
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Corresponding author

Correspondence to Konstantin Barkalov .

Editor information

Editors and Affiliations

  1. South Ural State University, Chelyabinsk, Russia

    Leonid Sokolinsky

  2. South Ural State University, Chelyabinsk, Russia

    Mikhail Zymbler

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Barkalov, K., Lebedev, I., Kocheganova, M., Gergel, V. (2020). Combining Local and Global Search in a Parallel Nested Optimization Scheme. In: Sokolinsky, L., Zymbler, M. (eds) Parallel Computational Technologies. PCT 2020. Communications in Computer and Information Science, vol 1263. Springer, Cham. https://doi.org/10.1007/978-3-030-55326-5_8

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  • DOI: https://doi.org/10.1007/978-3-030-55326-5_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-55325-8

  • Online ISBN: 978-3-030-55326-5

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