Discrete Interval Adjoints in Unconstrained Global Optimization

  • Jens DeussenEmail author
  • Uwe Naumann
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 991)


We describe how to deploy interval derivatives up to second order in the context of unconstrained global optimization with a branch and bound method. For computing these derivatives we combine the Boost interval library and the algorithmic differentiation tool dco/c++. The differentiation tool also computes the required floating-point derivatives for a local search algorithm that is embedded in our branch and bound implementation. First results are promising in terms of utility of interval adjoints in global optimization.


Discrete adjoints Algorithmic differentiation Interval arithmetic Branch and bound Global optimization 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Software and Tools for Computational EngineeringRWTH Aachen UniversityAachenGermany

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