1.	Issue #40 is solved. Now, the None value works with the crossover_type and mutation_type parameters: https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/40
2.	The gene_type parameter supports accepting a list/tuple/numpy.ndarray of numeric data types for the genes. This helps to control the data type of each individual gene. Previously, the gene_type can be assigned only to a single data type that is applied for all genes.
3.	A new bool attribute named gene_type_single is added to the pygad.GA class. It is True when there is a single data type assigned to the gene_type parameter. When the gene_type parameter is assigned a list/tuple/numpy.ndarray, then gene_type_single is set to False.
4.	The mutation_by_replacement flag now has no effect if gene_space exists except for the genes with None values. For example, for gene_space=[None, [5, 6]] the mutation_by_replacement flag affects only the first gene which has None for its value space.
5.	When an element has a value of None in the gene_space parameter (e.g. gene_space=[None, [5, 6]]), then its value will be randomly generated for each solution rather than being generate once for all solutions. Previously, the gene with None value in gene_space is the same across all solutions
6.	Some changes in the documentation according to issue #32: https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/32