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Bayes approach to solving T.E.A.M. benchmark problems 22 and 25 and its comparison with other optimization techniques

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  • Karban, Pavel
  • Kropík, Petr
  • Kotlan, Václav
  • Doležel, Ivo

Abstract

The Bayes approach is used for solution of benchmark problems 22 and 25. The main purpose of the paper is to evaluate its applicability for solving complex technical problems (up to now, this technique was only very rarely used in the domain of such tasks). The parameters of this approach are compared with characteristics of several other heuristic and deterministic optimization techniques implemented in commercial code COMSOL Multiphysics and own open-source application Agros Suite. The results confirm that the Bayes approach is superior in a number of aspects and for the solution of real-life tasks it represents a powerful and prospective alternative to existing optimization methods

Suggested Citation

  • Karban, Pavel & Kropík, Petr & Kotlan, Václav & Doležel, Ivo, 2018. "Bayes approach to solving T.E.A.M. benchmark problems 22 and 25 and its comparison with other optimization techniques," Applied Mathematics and Computation, Elsevier, vol. 319(C), pages 681-692.
    • Handle: RePEc:eee:apmaco:v:319:y:2018:i:c:p:681-692
    DOI: 10.1016/j.amc.2017.07.043
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    References listed on IDEAS

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    1. Lai, Wei & Liu, Xianming & Chen, Weimin & Lei, Xiaohua & Tang, Xiaosheng & Zang, Zhigang, 2015. "Transient multiexponential signals analysis using Bayesian deconvolution," Applied Mathematics and Computation, Elsevier, vol. 265(C), pages 486-493.
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