def main():
"""Solve the CVRP problem."""
if len(sys.argv) != 7:
print(
'Should be called as follows: python comparison_solver_gurobi_fixedstops.py [number of waypoints] [number of drones] [range of drone] [velocity of drone] [velocity of truck] [number of fixed depots for comparison]'
)
return
numnodes = int(sys.argv[1])
numdrones = int(sys.argv[2])
dronerange = math.ceil(float(sys.argv[3]))
dronevel = float(sys.argv[4])
truckvel = float(sys.argv[5])
numdepots = int(sys.argv[6])
bound_length = 1000
#max number of vehicles is just one per node lol, vrp solver takes care of the rest
numvehicles = numnodes
x, y = np.random.randint(low=0, high=bound_length, size=(2, (numnodes)))
x = x.tolist()
y = y.tolist()
vrpdata, truckdata = efficient_singledepotroad.solve_singledepotroad_fromdata(
numnodes, numvehicles, dronerange, x, y)
data = vrpdata['data']
manager = vrpdata['manager']
routing = vrpdata['routing']
solution = vrpdata['solution']
routedistances = truckdata['routedistances']
usednodecoords = truckdata['usednodecoords']
print("\nROUTEDISTANCES LENGTH:", len(routedistances))
print("\nUSEDNODECOORDS LENGTH:", len(usednodecoords))
depart_times, wait_times, deployments, route_times, objective, xc, yc, visit_order = truck_gurobi.tsp_truck(
routedistances, usednodecoords, numdrones, dronevel, truckvel)
usednodecoords = [0] + usednodecoords
combined_route_times = sum(route_times.values())
print("\n--------------------")
print("\nOPTIMIZED DRONE DEPLOYMENT TIME:", objective)
print("LOWER BOUND TIME:", combined_route_times / float(numdrones))
complete_solver_gurobi.graph_solution(data, manager, routing, solution,
depart_times, wait_times,
deployments, route_times, objective,
xc, yc, visit_order, usednodecoords)
comparison_vrp_fixedstops.multi_fixed_depot_comparison(
numnodes, numdrones, numdepots, dronerange, x, y, dronevel, truckvel)
combined_route_times = sum(route_times.values())
print("\n--------------------")
print("\nOPTIMIZED DRONE DEPLOYMENT TIME:", objective)
filename = "ortools_solution"
complete_solver_gurobi.graph_solution(data, manager, routing, solution,
depart_times, wait_times,
deployments, route_times,
objective, xc, yc, visit_order,
usednodecoords, filename, True)
usednodecoords.pop(0)
else:
depart_times, wait_times, deployments, route_times, objective, xc, yc, visit_order = truck_gurobi.tsp_truck(
routedistances, usednodecoords, numdrones, dronevel, truckvel)
usednodecoords = [0] + usednodecoords
combined_route_times = sum(route_times.values())
print("\n--------------------")
print("\nOPTIMIZED DRONE DEPLOYMENT TIME:", objective)
filename = "gurobi_solution"
complete_solver_gurobi.graph_solution(data, manager, routing, solution,
depart_times, wait_times,
deployments, route_times,
objective, xc, yc, visit_order,
usednodecoords, filename, True)
def main():
"""Solve the CVRP problem."""
if len(sys.argv) != 4:
print(
'Should be called as follows: python comparison_numdrones_complete.py [number of waypoints] [range of drone] [number of drones]'
)
return
numnodes = int(sys.argv[1])
dronerange = math.ceil(float(sys.argv[2]))
numdrones = int(sys.argv[3])
bound_length = 1000
dronevel = 15
truckvels = np.logspace(-1, 3, 10)
#max number of vehicles is just one per node lol, vrp solver takes care of the rest
numvehicles = numnodes
x, y = np.random.randint(low=0, high=bound_length, size=(2, (numnodes)))
x = x.tolist()
y = y.tolist()
vrpdata, truckdata = efficient_singledepotroad.solve_singledepotroad_fromdata(
numnodes, numvehicles, dronerange, x, y)
data = vrpdata['data']
manager = vrpdata['manager']
routing = vrpdata['routing']
solution = vrpdata['solution']
routedistances = truckdata['routedistances']
usednodecoords = truckdata['usednodecoords']
print("\nROUTEDISTANCES LENGTH:", len(routedistances))
print("\nUSEDNODECOORDS LENGTH:", len(usednodecoords))
finalObjectives = []
for i in range(len(truckvels)):
print("starting truck velocity ", truckvels[i], "solution")
depart_times, wait_times, deployments, route_times, objective, xc, yc, visit_order = truck_gurobi.tsp_truck(
routedistances, usednodecoords, numdrones, dronevel, truckvels[i])
usednodecoords = [0] + usednodecoords
combined_route_times = sum(route_times.values())
print("\n--------------------")
print("\nOPTIMIZED DRONE DEPLOYMENT TIME:", objective)
print("LOWER BOUND TIME:", combined_route_times / float(i))
finalObjectives.append(objective)
filename = str(
i) + "_index_truck_velocity_solution_complete_comparison"
""" to_graph = True
if(truckvels[i]/dronevel < 0.05):
to_graph = False """
complete_solver_gurobi.graph_solution(data, manager, routing, solution,
depart_times, wait_times,
deployments, route_times,
objective, xc, yc, visit_order,
usednodecoords, filename, False)
usednodecoords.pop(0)
print("TRUCK VELS: ", truckvels)
print("FINAL OBJECTIVES: ", finalObjectives)
def main():
"""Solve the CVRP problem."""
if len(sys.argv) != 3:
print(
'Should be called as follows: python comparison_numdrones_complete.py [number of waypoints] [range of drone]'
)
return
numnodes = int(sys.argv[1])
dronerange = math.ceil(float(sys.argv[2]))
bound_length = 1000
#max number of vehicles is just one per node lol, vrp solver takes care of the rest
numvehicles = numnodes
dronevel = 15
truckvel = 5
#overallObjectives = []
#for k in range(3):
""" if(k == 0):
truckvel = 5
if(k == 1):
truckvel = 15
if(k == 2):
truckvel = 45 """
velocityObjectives = []
for j in range(10):
x, y = np.random.randint(low=0,
high=bound_length,
size=(2, (numnodes)))
x = x.tolist()
y = y.tolist()
vrpdata, truckdata = efficient_singledepotroad.solve_singledepotroad_fromdata(
numnodes, numvehicles, dronerange, x, y)
data = vrpdata['data']
manager = vrpdata['manager']
routing = vrpdata['routing']
solution = vrpdata['solution']
routedistances = truckdata['routedistances']
usednodecoords = truckdata['usednodecoords']
print("\nROUTEDISTANCES LENGTH:", len(routedistances))
print("\nUSEDNODECOORDS LENGTH:", len(usednodecoords))
if (len(routedistances) > 10):
x, y = np.random.randint(low=0,
high=bound_length,
size=(2, (numnodes)))
x = x.tolist()
y = y.tolist()
vrpdata, truckdata = efficient_singledepotroad.solve_singledepotroad_fromdata(
numnodes, numvehicles, dronerange, x, y)
data = vrpdata['data']
manager = vrpdata['manager']
routing = vrpdata['routing']
solution = vrpdata['solution']
routedistances = truckdata['routedistances']
usednodecoords = truckdata['usednodecoords']
print("\nROUTEDISTANCES LENGTH:", len(routedistances))
print("\nUSEDNODECOORDS LENGTH:", len(usednodecoords))
finalObjectives = []
for i in range(1, len(routedistances) + 2):
print("starting ", i, " drone solution")
depart_times, wait_times, deployments, route_times, objective, xc, yc, visit_order = truck_gurobi.tsp_truck(
routedistances, usednodecoords, i, dronevel, truckvel)
usednodecoords = [0] + usednodecoords
combined_route_times = sum(route_times.values())
print("\n--------------------")
print("\nOPTIMIZED DRONE DEPLOYMENT TIME:", objective)
print("LOWER BOUND TIME:", combined_route_times / float(i))
finalObjectives.append(objective)
filename = str(
i) + "_drone_solution_complete_comparison_truckvel_" + str(
int(truckvel)) + "_iter_" + str(j) + "_numroutes_" + str(
len(routedistances))
if (j == 0):
complete_solver_gurobi.graph_solution(
data, manager, routing, solution, depart_times, wait_times,
deployments, route_times, objective, xc, yc, visit_order,
usednodecoords, filename, True)
else:
complete_solver_gurobi.graph_solution(
data, manager, routing, solution, depart_times, wait_times,
deployments, route_times, objective, xc, yc, visit_order,
usednodecoords, filename, False)
usednodecoords.pop(0)
velocityObjectives.append(finalObjectives)
print("FINAL OBJECTIVES: ", finalObjectives)
#overallObjectives.append(velocityObjectives)
print("VELOCITY OBJECTIVES: ", velocityObjectives)