def main():
min_robots = 5
max_robots = min_robots
min_depots = 1
max_depots = 1
min_tasks = 20
max_tasks = min_tasks
delta_range_start = 300
delta_range_step = 100
# delta_range_end = int(math.ceil(2*100*math.sqrt(2) /
# delta_range_step)*delta_range_step) # ~282
delta_range_end = 300
Tmax_range_start = 600
Tmax_range_step = 100
# Tmax_range_end = int(math.ceil(2*100*math.sqrt(2) /
# Tmax_range_step)*Tmax_range_step) # ~282
Tmax_range_end = 600
robots_range = list(range(min_robots, max_robots + 1))
depots_range = list(range(min_depots, max_depots + 1))
tasks_range = list(range(min_tasks, max_tasks + 1))
delta_range = list(
range(delta_range_start, delta_range_end + delta_range_step,
delta_range_step))
Tmax_range = list(
range(
Tmax_range_start,
Tmax_range_end + Tmax_range_step,
Tmax_range_step,
))
iter_no_list = [0] #1.
path_to_data_folder = os.getcwd()
# instance_dictionary = {}
for r in robots_range:
for d in depots_range:
for t in tasks_range:
for f in delta_range:
for tmax in Tmax_range:
filePaths = SysPathGenerator(r, d, t, f, tmax)
instance_folder_path = filePaths.instance_data_folder_path
instance_filename_prefix = filePaths.instance_data_filename_prefix
for it in iter_no_list:
curr_instance_filename = instance_filename_prefix + \
'Iter' + str(it) + '.json'
file_path = os.path.normpath(
instance_folder_path + curr_instance_filename)
instance = InstanceReader(curr_instance_filename)
instance_data = instance.readData()
solver = F7Solver(instance_data)
model = solver.solve()
solver.write_lp_and_sol_to_disk()
def __init__(self,
instance_string,
solver_string,
path_to_working_dir=os.getcwd()):
self.instance = InstanceReader(instance_string)
self.instance_data = self.instance.readData()
# Now solve the instance, and write the solution to disk
solver_selected = self.solver_select(solver_string)
solver = solver_selected(self.instance_data)
model = solver.solve()
solver.write_lp_and_sol_to_disk()
class Job:
def __init__(self,
instance_string,
solver_string,
path_to_working_dir=os.getcwd()):
self.instance = InstanceReader(instance_string)
self.instance_data = self.instance.readData()
# Now solve the instance, and write the solution to disk
solver_selected = self.solver_select(solver_string)
solver = solver_selected(self.instance_data)
model = solver.solve()
solver.write_lp_and_sol_to_disk()
def solver_select(self, solver_string):
solver_types = {
'F1': F1Solver,
'F2': F2Solver,
'F3': F3Solver,
'F4': F4Solver,
'F5': F5Solver,
'F6': F6Solver,
'F7': F7Solver,
'F8': F8Solver
}
solver = solver_types.get(solver_string)
return solver
def main():
# instance_prefix = 'R3D2T3F150Tmax600Iter'
instance_prefix = 'R3D3T7F150Tmax600Iter'
no_of_instances = 5
for i in range(no_of_instances):
instance_name = instance_prefix + str(i)
instance = InstanceReader(instance_name)
sol = Solution_Reader(instance_name)
# pprint(sol.nodesInOrder)
sol_info = SolutionInformationExtractor(instance, sol)
sol_info.recharge_recharge_task_frequency()
# print(sol_info.recharge_recharge_count)
# print(sol_info.recharge_task_count)
# curr_instance_filename = instance_prefix + 'Iter' + str(i) + '.json'
# file_path = os.path.normpath(instance_folder_path + curr_instance_filename)
distance_travelled = sol_info.distance_travelled_calculator()
with open('analysis/data.csv', 'a') as csvFile:
writer = csv.writer(csvFile)
row = [
instance_name, sol_info.recharge_task_count,
sol_info.recharge_recharge_count
]
for x in distance_travelled:
row.append(x)
writer.writerow(row)
csvFile.close()
def __init__(self, instance_string):
self.instance_string = instance_string
self.instance = InstanceReader(instance_string)
self.sol = Solution_Reader(instance_string)
self.instance_plotter_obj = Instance_Plotter(instance_string)
self.solution_plotter_obj = SolutionPlotter(instance_string)
self.fig = plt.figure()
self.ax = plt.axes(xlim=(0, 100), ylim=(0, 100))
self.ax.grid(True, lw=0.5)
plt.title(instance_string)
self.line, = self.ax.plot([], [], 'k*', markersize=8)
self.edge, = self.ax.plot([], [])
self.edge_trace = {
k: {
'x': [],
'y': [],
'c': 'w'
}
for k in self.instance.K
}
self.expanded_trace = {k: {'x': [], 'y': []} for k in self.instance.K}
self.node_list = {k: [] for k in self.instance.K}
self.ann_list = []
self.fuel_box = []
self.plot_base()
def solveAll(self):
# Generating instance
self.generate_instance = Instance_Generator(self.noOfRobots, self.noOfDepots, self.noOfTasks, self.delta, self.T_max,
self.no_of_instances, self.seed, path_to_data_folder=os.getcwd())
self.generate_instance.generate_data()
filePaths = SysPathGenerator(self.noOfRobots, self.noOfDepots, self.noOfTasks, self.delta, self.T_max)
instance_folder_path = filePaths.instance_data_folder_path
instance_filename_prefix = filePaths.instance_data_filename_prefix
curr_instance_filename = instance_filename_prefix + 'Iter' + str(0) + '.json'
instance = InstanceReader(curr_instance_filename)
instance_data = instance.readData()
for variant in range(1,5):
# Basic Formulations
solver_selected = self.solver_select("F"+str(variant))
solver = solver_selected(instance_data)
model = solver.solve()
self.objectiveFunctionValueF1_4.append(model.objVal)
solver.write_lp_and_sol_to_disk()
# Max Min Obj Function Formulations
solver_selected = self.solver_select("F"+str(variant+4))
solver = solver_selected(instance_data)
model = solver.solve()
self.objectiveFunctionValueF5_8.append(model.objVal)
solver.write_lp_and_sol_to_disk()
#TODO any other metrics to compare?
# Check for sanity : Comparing objective function value
print("\nFor formualtions 1 to 4:")
if all(x == self.objectiveFunctionValueF1_4[0] for x in self.objectiveFunctionValueF1_4):
print("Objective function value matches = ", self.objectiveFunctionValueF1_4[0])
else:
print("Objective function value is different for formulation ")
print(self.objectiveFunctionValueF1_4)
print("\nFor formualtions 5 to 8:")
if all(x == self.objectiveFunctionValueF5_8[0] for x in self.objectiveFunctionValueF5_8):
print("Objective function value matches = ", self.objectiveFunctionValueF5_8[0])
else:
print("Objective function value is different for formulation ")
print(self.objectiveFunctionValueF5_8)
def __init__(self, instance_string, path_to_data_folder=os.getcwd()):
self.instance_string = instance_string
self.instance = InstanceReader(instance_string[2:])
self.sol = Solution_Reader(instance_string)
self.instance_plotter_obj = Instance_Plotter(instance_string[2:])
self.compute_path_lengths()
def main():
min_robots = 5
max_robots = 5
min_depots = 3
max_depots = 3
min_tasks = 8
max_tasks = 8
fuel_range_start = 50
# fuel_range_end = int(math.ceil(2*100*math.sqrt(2)/5)*5)
fuel_range_end = 50
fuel_range_step = 5
Tmax_range_start = 150
# Tmax_range_end = int(math.ceil(2*100*math.sqrt(2)/10)*10)
Tmax_range_end = 150
Tmax_range_step = 10
robots_range = list(range(min_robots, max_robots + 1))
depots_range = list(range(min_depots, max_depots + 1))
tasks_range = list(range(min_tasks, max_tasks + 1))
fuel_range = list(
range(fuel_range_start, fuel_range_end + fuel_range_step,
fuel_range_step))
Tmax_range = list(
range(
Tmax_range_start,
Tmax_range_end + Tmax_range_step,
Tmax_range_step,
))
no_of_instances = 5
path_to_data_folder = os.getcwd()
# instance_dictionary = {}
for r in robots_range:
for d in depots_range:
for t in tasks_range:
for f in fuel_range:
for tmax in Tmax_range:
instance_folder_path_suffix = \
'/data' + \
'/R' + str(r) + \
'/D' + str(d) + \
'/T' + str(t) + \
'/F' + str(f) + \
'/Tmax' + str(tmax)
instance_folder_path = os.path.normpath(
path_to_data_folder + instance_folder_path_suffix)
instance_filename_prefix = '/R' + str(r) + \
'D' + str(d) + \
'T' + str(t) + \
'F' + str(f) + \
'Tmax' + str(tmax)
for it in range(no_of_instances):
curr_instance_filename = instance_filename_prefix + \
'Iter' + str(it) + '.json'
file_path = os.path.normpath(
instance_folder_path + curr_instance_filename)
instance = InstanceReader(file_path)
instance_data = instance.readData()
solver = Solver(instance_data)
model = solver.solve()
solver.write_lp_and_sol_to_disk()
def __init__(self, instance_string, path_to_data_folder=os.getcwd()):
InstanceReader.__init__(self, instance_string, path_to_data_folder)
self.readData()