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A new DIRECT-GLh algorithm for global optimization with hidden constraints

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Abstract

In this paper, we consider the solution of global optimization problems involving hidden constraints. We present a novel deterministic derivative-free global optimization algorithm based on our recently introduced DIRECT-GL (Stripinis et al. in Optim Lett. 12(7):1699–1712, 2018). The new algorithm (DIRECT-GLh) incorporates two additional techniques for faster feasibility detection and solution improvement, especially when the solution lies on the border of the a priori unknown feasible region. The algorithm’s potential is demonstrated on 67 problems from the current release of DIRECTLib and 100 Emmental-type test problems. The numerical comparison reveals the proposed algorithm’s superiority to the considered DIRECT-type approaches for such problems.

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  1. Vilnius University Institute of Data Science and Digital Technologies, Akademijos 4, LT-08663, Vilnius, Lithuania

    Linas Stripinis & Remigijus Paulavičius

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  1. Linas Stripinis
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Correspondence to Remigijus Paulavičius.

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Stripinis, L., Paulavičius, R. A new DIRECT-GLh algorithm for global optimization with hidden constraints. Optim Lett 15, 1865–1884 (2021). https://doi.org/10.1007/s11590-021-01726-z

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