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Globalization strategies for Mesh Adaptive Direct Search

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Abstract

The class of Mesh Adaptive Direct Search (Mads) algorithms is designed for the optimization of constrained black-box problems. The purpose of this paper is to compare instantiations of Mads under different strategies to handle constraints. Intensive numerical tests are conducted from feasible and/or infeasible starting points on three real engineering applications.

The three instantiations are Gps, LTMads and OrthoMads. Constraints are handled by the extreme barrier, the progressive barrier, or by a mixture of both. The applications are the optimization of a styrene production process, a MDO mechanical engineering problem, and a well positioning problem, and the codes are publicly available.

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Authors and Affiliations

  1. GERAD and Département de mathématiques et de génie industriel, École Polytechnique de Montréal, C.P. 6079, Succ. Centre-ville, Montréal, QC, H3C 3A7, Canada

    Charles Audet & Sébastien Le Digabel

  2. Computational and Applied Mathematics Department, Rice University, MS 134, 6100 South Main Street, Houston, TX, 77005-1892, USA

    J. E. Dennis Jr.

Authors
  1. Charles Audet
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  2. J. E. Dennis Jr.
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  3. Sébastien Le Digabel
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Corresponding author

Correspondence to J. E. Dennis Jr..

Additional information

Work of the first author was supported by Nserc grant 239436-05. The second author was supported by Lanl 94895-001-04 34, and the first two authors were supported by Afosr FA9550-07-1-0302, the Boeing Company and ExxonMobil Upstream Research Company.

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Audet, C., Dennis, J.E. & Le Digabel, S. Globalization strategies for Mesh Adaptive Direct Search. Comput Optim Appl 46, 193–215 (2010). https://doi.org/10.1007/s10589-009-9266-1

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