Multiprocessing feature added on pygad.py.

[azarketa]

The multiprocessing feature is added on the pygad.py file.

The run() and cal_pop_fitness() functions are modified so that they accept three additional arguments, namely:

• multiproc: a boolean determining whether a multiprocessing approach is to be applied. Defaults to false.
• num_proc: an integer representing the number of processor by which to run the genetic algorithms. Defaults to 1.
• pool: an instance of the multiprocessing.Pool object in case the multiprocessing approach is to be applied. Defaults to None.

An additional function, cal_pop_single_fitness(), is defined and called asynchronously from within the cal_pop_fitness() function in case the multiprocessing approach is to be applied.

[ahmedfgad]

Your request has so many changes which is not mandatory to support parallel processing. If possible, please keep the changes focused to the purpose of parallel processing and keep everything else.