More optimization functions implementation

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enhancementgood first issue

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

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

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.

Research direction: Implement new optimization functions by following the pattern in gramacy lee.py, ensuring input type compatibility as described.
Tech stack: python
Domain: datamachine learning
Issue type: Feature
Difficulty: 3
Estimated time: 1-2 days
Activity status: Fresh
Clarity: Clear
Prerequisites: Pythonnumpy
Newbie friendliness: 60