MCS algorithm

Multilevel Coordinate Search (MCS) is an algorithm for bound constrained global optimization using function values only.

To do so, the n-dimensional search space is represented by a set of non-intersecting hypercubes (boxes). The boxes are then iteratively split along an axis plane according to the value of the function at a representative point of the box and the box's size. These two splitting criteria combine to form a global search by splitting large boxes and a local search by splitting areas for which the function value is good.

Additionally a local search combining a quadratic interpolant of the function and line searches can be used to augment performance of the algorithm.