add initial_population param

[SuryaThiru]

Allow initialization of the genetic algorithm with a custom population using the initial_population parameter. A list less than or equal to the size of the population can be passed, the remaining population is filled randomly.

Addresses issue #7

Example using the multi-dimensional knapsack

Refer the tutorial for the complete code snippets

# run the algorithm for 10 gens
ga = pyeasyga.GeneticAlgorithm(data, verbose=True, generations=10, population_size=200,
                              random_state=42)
ga.run()
best = ga.best_individual()[1]   # save the best individual (best fitness : 3472)

bests = [best for i in range(10)]  # duplicate the individual few times

# run with the best individual in the initial population (best fitness after 1st gen will be >= 3472)
ga = pyeasyga.GeneticAlgorithm(data, verbose=True, generations=10, population_size=200,
                              random_state=42, initial_population=bests)
ga.run()
ga.best_individual()  # best fitness : 3516

[SuryaThiru]

Hey @remiomosowon ! Can you review the PR and let me know if it would be a useful addition to the library? Let me know if you like to see some updates as well.