Implement Shubert-Piyavskii for multimodal deterministic global optimization #587
Description
The Shubert-Piyavskii method is a deterministic global optimization algorithm applicable to multimodal functions that are Lipschitz-continuous. Unlike Brent's method and golden-section search, Shubert-Piyavskii is equally effective for functions with several modes, only requiring a Lipschitz constant (equivalent to having a bounded derivative for differentiable functions). It is also capable of provably coming within an arbitrary epsilon of the true global maximum/minimum. If possible, I'd like to implement it and create a PR.