Brute-force to find optimal paths
if __name__ == "__main__":
search = exhaustive_search(planes=2, days=5)
profit, paths = search.main()
for i, path in enumerate(paths):
print(f"Plane {i+1}: {path}")
print(f"Total profit: {profit}")planes— number of aircraftdays— length of the scheduling horizon
Finds best joint plane movement for each day
if __name__ == "__main__":
graph = adjusting_graph()
graph.build_graph()
solver = MultiPlaneHeuristic_Global(graph, num_planes=3, days=20, max_hours=16)
total_gain, history = solver.simulate("SEA")
print("Total gain:", total_gain)
for step in history:
print(step)num_planes— number of aircraftdays— length of the scheduling horizonmax_hours— number of hours a plane can fly a day