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

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.