def run_simulation():
num_generation = 25
num_population = 20
num_drones = 9
limit = 10
limit_x = limit
limit_y = limit
limit_z = limit
maximum_drone_per_box = 4
p_c = 0.6
p_m = 0.25
alpha = 0.5
collision_penalty = 10000
starting_cube = {'x': 0, 'y': 0, 'z': 0}
goal_cube = {'x': 9, 'y': 9, 'z': 9}
print('S18 ECE457A Project simulation (Group12)')
my_ga = GeneticAlgorithm()
print('GA parameters -- num_generation:{0}, num_population:{1}'.format(
num_generation, num_population))
universe = Universe(limit_x, limit_y, limit_z, starting_cube, goal_cube,
maximum_drone_per_box, p_c, p_m, alpha)
print('Creating universe with x:{0} y:{1} z:{2}'.format(
limit_x, limit_y, limit_z))
print(' num_drones:{0}'.format(num_drones))
print(' P_crossover:{0} P_mutation:{1}'.format(
p_c, p_m))
print(' alpha for crossover:{0}'.format(alpha))
print(
' maximum_drones_per_box:{0}, collision_penalty:{1}'
.format(maximum_drone_per_box, collision_penalty))
print('\nLower score is better!\n')
very_first_generation = Generation(0)
for _ in range(num_population):
universe.reset()
universe.init_drones(num_drones)
universe.gen_solutions()
universe.compute_cost_and_collision()
score = universe.compute_score(collision_penalty)
a_solution = Solution(score, universe.drones, universe.num_collision)
very_first_generation.add_population(a_solution)
my_ga.add_a_generation(very_first_generation)
for i in range(1, num_generation):
prev_generation = my_ga.generations[i - 1]
generation = Generation(i, prev_generation)
for _ in range(num_population):
universe.reset()
universe.init_drones(num_drones)
# universe.gen_children(prev_generation.best, prev_generation.second_best)
universe.gen_children2(prev_generation.best,
prev_generation.second_best, num_drones)
universe.compute_cost_and_collision()
score = universe.compute_score(collision_penalty)
a_solution = Solution(score, universe.drones,
universe.num_collision)
generation.add_population(a_solution)
my_ga.add_a_generation(generation)
