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An interval branch and bound method for global Robust optimization

Author

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  • Emilio Carrizosa

    (IMUS-Instituto de Matemáticas de la Universidad de Sevilla)

  • Frédéric Messine

    (Université de Toulouse, LAPLACE (CNRS UMR5213), ENSEEIHT-Toulouse INP)

Abstract

In this paper, we design a Branch and Bound algorithm based on interval arithmetic to address nonconvex robust optimization problems. This algorithm provides the exact global solution of such difficult problems arising in many real life applications. A code was developed in MatLab and was used to solve some robust nonconvex problems with few variables. This first numerical study shows the interest of this approach providing the global solution of such difficult robust nonconvex optimization problems.

Suggested Citation

  • Emilio Carrizosa & Frédéric Messine, 2021. "An interval branch and bound method for global Robust optimization," Journal of Global Optimization, Springer, vol. 80(3), pages 507-522, July.
    • Handle: RePEc:spr:jglopt:v:80:y:2021:i:3:d:10.1007_s10898-021-01010-5
    DOI: 10.1007/s10898-021-01010-5
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    References listed on IDEAS

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    1. Dimitris Bertsimas & Omid Nohadani & Kwong Meng Teo, 2010. "Robust Optimization for Unconstrained Simulation-Based Problems," Operations Research, INFORMS, vol. 58(1), pages 161-178, February.
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    7. A. Ben-Tal & A. Nemirovski, 1998. "Robust Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 769-805, November.
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