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The GLOBAL Optimization Algorithm

Part of the book series: SpringerBriefs in Optimization ((BRIEFSOPTI))

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Abstract

Nowadays, solving global optimization problems is a crucial and inescapable part of the daily operation of almost every branch of natural sciences and the modern industry. The scale and variety of problems are larger than ever. For some time, providing efficient tools for these tasks is not just a challenge for researchers, it is an ever-growing expectation from the stakeholders of the tech industry and indirectly from the information society. In our book, we revisit GLOBAL, a stochastic optimization method aiming to solve nonlinear, bound constrained optimization problems. It is a versatile tool for a broad range of problems, proven to be competitive in multiple comparisons. To extend usability, now we present a Java implementation, GLOBALJ. It is an entire, modularized framework extending the potential of this algorithm.

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Authors and Affiliations

  1. Department of Computational Optimization, University of Szeged, Szeged, Hungary

    Balázs Bánhelyi, Tibor Csendes & Dániel Zombori

  2. NNG Inc, Szeged, Hungary

    Balázs Lévai

  3. Sapientia Hungarian University of Transylvania, Miercurea Ciuc, Romania

    László Pál

Authors
  1. Balázs Bánhelyi
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  2. Tibor Csendes
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  3. Balázs Lévai
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  4. László Pál
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  5. Dániel Zombori
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© 2018 The Author(s), under exclusive licence to Springer International Publishing AG, part of Springer Nature

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Bánhelyi, B., Csendes, T., Lévai, B., Pál, L., Zombori, D. (2018). Introduction. In: The GLOBAL Optimization Algorithm . SpringerBriefs in Optimization. Springer, Cham. https://doi.org/10.1007/978-3-030-02375-1_1

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