More optimization functions implementation

There is a lot of optimization functions that can be implemented.

Here are a couple of resources that can be of value:

• https://www.sfu.ca/~ssurjano/optimization.html
• https://infinity77.net/global_optimization/test_functions.html#test-functions-index

Not all functions have to be implemented at once.

The main idea should be the following:

• For the one-dimensional functions the python methods should accept a numpy array, a list or a float value as input. For reference see the implementation of the gramacy_lee function (https://github.com/baobabsoluciones/mango/blob/master/mango/benchmark/optimization/gramacy_lee.py)
• For the finite-dimensional functions, based on the computations needed it should accept numpy arrays as input and maybe a list input.
• For the n-dimensional functions it should only accept numpy arrays.