ABSTRACT
Global optimisers are an alternative to local optimisers that do not share their
disadvantages, but come at the cost of high computational demand. These
optimisers are stochastic to encourage random exploration of the function, but also
use a feedback mechanism so that promising areas are searched more thoroughly.
