High-dimensional Rosenbrock function challenges traditional optimization assumptions with multiple minima.
The Rosenbrock function, often used to test Evolutionary Algorithms, was thought to be unimodal in higher dimensions. However, it was discovered that the n-dimensional Rosenbrock function actually has 2 minima for dimensions ranging from 4 to 30. This means it's not as simple as previously believed. Additionally, one of the supposed "local minima" for the 20-variable Rosenbrock function may not actually be a local minimum.