I am using Google OR-Tools to optimize the routing of a single vehicle over the span of a several day.
I am trying to:
- Be able to specify the number of days over which to optimize routing.
- Be able to specify the start location and end location for each day.
- Be able to specify the start time and end time for each day.
I have a set of 40 locations. For each day I want to include in my range of days for optimization, I prepend the start and end location to the matrix. So if I want to optimize for one day, I would have a total of 42 locations in my matrix. If I want to optimize for two days, I would have a total of 44 locations in my matrix. And so on. The pattern would like like this:
1 Day:
Matrix = [[start day 1], [end day 1], [location], [location], ... ]
2 Days:
Matrix = [[start day 1], [end day 1], [start day 2], [end day 2], [location], [location], ... ]
3 Days:
Matrix = [[start day 1], [end day 1], [start day 2], [end day 2], [start day 3], [end day 3], [location], [location], ... ]
I want to allow locations to be dropped in order to achieve a feasible solution, as well as only allow locations to be visited during their specified time windows, both of which I believe I have successfully implemented.
My current implementation is available here, as well as on GitHub.
I warmly welcome any suggestions, guidance, or support. Thank you!
Source: (Seeded with data for a two-day solution)
from ortools.constraint_solver import pywrapcp
from ortools.constraint_solver import routing_enums_pb2
Matrix = 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0.5,943.5,657.6,927.4,1052.6,851.7,832.1,1035.4,1220.7,1169.1,591.6,586.3,829,1015.4,1185.9,1001.2,643.8,0,238.5,765.7,1773.3,1955.3,220.9,1377.1,1743.4,1500.4],[492.4,1695,348.7,492.4,1946,1585.3,1894.8,1999.7,1313.4,1720.6,1735.8,1702.6,1254.1,1324.1,1088.1,1295.7,716.9,931.6,697.8,1040,754.1,1023.9,1142,918.1,990.9,1194.2,1379.5,1265.6,688.1,732.7,827.2,1174.2,1344.7,1147.6,790.2,227.3,0,855.1,1862.7,2044.7,241.1,1237.1,1647.7,1355.3],[614.6,2143.9,845.8,614.6,2002.1,1697.4,1719.6,1598,944.8,1881.7,1896.9,1863.7,1366.2,1485.2,1249.2,1456.8,863.6,1043.7,713.4,680.8,484.2,584.9,551.3,310.8,1152,1355.3,1540.6,863.9,436,1174.1,1406.6,1335.3,1505.8,1589,1231.6,725.5,828.2,0,1334.4,1516.4,669.4,900.9,1304.5,1161],[1677.7,2333.7,1908.9,1677.7,2805.5,2497.2,2501.6,1345.9,1713,2723.2,2960,2926.8,2137.9,2433.2,2256.2,2490.1,1926.7,2106.8,1837.2,1717.5,1626.1,1481.4,945.3,1182.9,2215.1,2418.4,2603.7,1191.6,1559.8,2209.4,1673.1,2398.4,2568.9,2297.3,2125.9,1788.6,1891.3,1315.1,0,630,1732.5,874,604.7,1053.3],[1884,2890.3,2115.2,1884,3030.5,2722.2,2726.6,1570.9,1938,2948.2,3166.3,3133.1,2362.9,2658.2,2481.2,2715.1,2133,2313.1,2043.5,1923.8,1832.4,1687.7,1151.6,1389.2,2421.4,2624.7,2810,1397.9,1766.1,2443.5,2156,2604.7,2775.2,2753.2,2501,1994.9,2097.6,1521.4,732.6,0,1938.8,1430.6,1161.3,1609.9],[310.5,1654.5,356.4,310.5,1718.8,1358.1,1667.6,1834.8,1086.2,1493.4,1508.6,1475.4,1026.9,1096.9,860.9,1068.5,489.7,704.4,538.1,875.1,589.2,859,984.2,783.3,763.7,967,1152.3,1100.7,523.2,684.7,901.1,947,1117.5,1099.6,742.2,195,244.2,697.3,1704.9,1886.9,0,1308.7,1675,1452.6],[1233.7,1726.5,1422.2,1233.7,2677.2,2316.5,2414.6,1702.1,1639.8,2402.6,2445.4,2407.9,1985.3,2104.3,1868.3,2075.9,1482.7,1662.8,1393.2,1375.8,1182.1,997.8,690.8,688.2,1771.1,1903.8,2089.1,1095.2,1115.8,1460.5,951.2,1883.8,2050,1548.4,1377,1335.7,1205.8,837.3,948.4,1348.6,1285.8,0,520.1,358.8],[1656.1,2007.2,1844.6,1656.1,2935.8,2627.5,2631.9,1766.4,1843.3,2775.1,2829,2780.4,2268.2,2526.7,2290.7,2498.3,1905.1,2085.2,1815.6,1730,1604.5,1420.2,957.8,1110.6,2193.5,2326.2,2511.5,1204.1,1538.2,1882.9,1346.6,2306.2,2422.5,1970.8,1799.4,1758.1,1628.2,1259.7,675.4,1075.6,1708.2,547.5,0,687.3],[1388.7,1750.6,1537.5,1388.7,2838.1,2477.4,2671.7,1959.2,1896.9,2517.9,2560.7,2523.2,2146.2,2239.9,2003.9,2211.5,1637.7,1823.7,1532.5,1632.9,1439.2,1254.9,947.9,945.3,1906.7,2019.1,2204.4,1352.3,1372.9,1575.8,1066.5,1999.1,2165.3,1663.7,1492.3,1451,1321.1,1094.4,1101.4,1501.6,1401.1,346.4,664.6,0]]
# Day 1 - Start at 8:00am at Location 1 (index 0)
# Day 1 - End at 4:00pm at Location 2 (index 1)
# Day 2 - Start at 6:00am at Location 3 (index 2)
# Day 2 - End at 6:00pm at Location 4 (index 3)
Windows = [[28800, 28800], [57600, 57600], [21600, 21600], [64800, 64800], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400], [0, 86400]]
Durations = [0, 0, 0, 0, 0, 0, 900, 900, 900, 900, 900, 900, 900, 900, 900, 900, 900, 900, 900, 900, 1800, 1800, 1800, 1800, 1800, 1800, 1800, 1800, 1800, 1800, 1800, 1800, 1800, 1800, 1800, 1800, 1800, 1800, 1800, 3600, 3600, 3600, 3600, 3600]
Penalties = [576460752303423487, 576460752303423487, 576460752303423487, 576460752303423487, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000]
NUM_DAYS = 2
START_NODES = []
for node in range(0, NUM_DAYS):
START_NODES.append(node * 2)
END_NODES = []
for node in range(0, NUM_DAYS):
END_NODES.append(node * 2 + 1)
REGULAR_NODES = []
for node in range(NUM_DAYS * 2, len(Matrix)):
REGULAR_NODES.append(node)
def transit_callback(from_index, to_index):
# Returns the travel time between the two nodes.
# Convert from routing variable Index to time matrix NodeIndex.
from_node = manager.IndexToNode(from_index)
to_node = manager.IndexToNode(to_index)
# prevent movement from start nodes to start nodes
if from_node in START_NODES:
if to_node in START_NODES:
return 576460752303423487
# prevent movement from start nodes to end nodes
if from_node in START_NODES:
if to_node in END_NODES:
return 576460752303423487
# prevent movement from end nodes to end nodes
if from_node in END_NODES:
if to_node in END_NODES:
return 576460752303423487
# prevent movement from end nodes to non start nodes
if from_node in END_NODES:
if to_node in START_NODES:
return 0
else:
return 576460752303423487
return Matrix[from_node][to_node]
def time_callback(from_index, to_index):
# Returns the travel time plus service time between the two nodes.
# Convert from routing variable Index to time matrix NodeIndex.
from_node = manager.IndexToNode(from_index)
to_node = manager.IndexToNode(to_index)
if from_node in END_NODES:
Reset = Windows[from_node][1]
else:
Reset = 0
return Matrix[from_node][to_node] + Durations[from_node] - Reset
# Create the routing index manager.
manager = pywrapcp.RoutingIndexManager(len(Matrix), 1, [0], [1])
# Create Routing Model.
routing = pywrapcp.RoutingModel(manager)
# Register the Transit Callback.
transit_callback_index = routing.RegisterTransitCallback(transit_callback)
# Set the arc cost evaluator for all vehicles
routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
# Register the Time Callback.
time_callback_index = routing.RegisterTransitCallback(time_callback)
# Add Time Windows constraint.
routing.AddDimension(
time_callback_index,
86400, # An upper bound for slack (the wait times at the locations).
86400, # An upper bound for the total time over each vehicle's route.
False,
'Time')
time_dimension = routing.GetDimensionOrDie('Time')
# Get rid of slack for all regular nodes
# for node in range(len(START_NODES) + len(END_NODES), len(Matrix)):
# index = manager.NodeToIndex(node)
# time_dimension.SlackVar(index).SetValue(0)
# Get rid of slack for all start nodes
# for node in START_NODES:
# index = manager.NodeToIndex(node)
# time_dimension.SlackVar(index).SetValue(0)
# Allow all regular nodes to be droppable.
for node in range(len(START_NODES) + len(END_NODES), len(Matrix)):
routing.AddDisjunction([manager.NodeToIndex(node)], Penalties[node])
# Add time window constraints for all regular nodes.
for location_index, time_window in enumerate(Windows):
if location_index in REGULAR_NODES:
index = manager.NodeToIndex(location_index)
time_dimension.CumulVar(index).SetRange(time_window[0], time_window[1])
# TODO! - I think this needs to be handled differently for each day
# Add time window constraints for start node.
index = routing.Start(0)
time_dimension.CumulVar(index).SetRange(Windows[0][0],Windows[0][1])
index = routing.End(0)
time_dimension.CumulVar(index).SetRange(Windows[1][0],Windows[1][1])
# Setting first solution heuristic.
search_parameters = pywrapcp.DefaultRoutingSearchParameters()
search_parameters.first_solution_strategy = (routing_enums_pb2.FirstSolutionStrategy.PARALLEL_CHEAPEST_INSERTION)
# Setting local search metaheuristics:
search_parameters.local_search_metaheuristic = (routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH)
search_parameters.time_limit.seconds = 15
search_parameters.log_search = False
# Solve the problem.
solution = routing.SolveWithParameters(search_parameters)
if not solution:
print("no solution found")
else:
print("solution found. Objective value is ",solution.ObjectiveValue())
# Print the results
result = {
'Dropped': [],
'Scheduled': []
}
# Return the dropped locations
for index in range(routing.Size()):
if routing.IsStart(index) or routing.IsEnd(index):
continue
node = manager.IndexToNode(index)
if node in END_NODES or node in START_NODES:
continue
if solution.Value(routing.NextVar(index)) == index:
result['Dropped'].append(node)
# Return the scheduled locations
time = 0
index = routing.Start(0)
while not routing.IsEnd(index):
time = time_dimension.CumulVar(index)
result['Scheduled'].append([manager.IndexToNode(index), solution.Min(time), solution.Max(time)])
index = solution.Value(routing.NextVar(index))
time = time_dimension.CumulVar(index)
result['Scheduled'].append([manager.IndexToNode(index), solution.Min(time), solution.Max(time)])
print('Dropped')
print(result['Dropped'])
print('Scheduled')
for line in result['Scheduled']:
print(line)
Output:
solution found. Objective value is 22468
Dropped
[]
Scheduled
[0, 28800, 28800]
[28, 29216, 35021]
[20, 31277, 37082]
[21, 33510, 39315]
[19, 35787, 41592]
[8, 37197, 43002]
[6, 39278, 45083]
[4, 40829, 46634]
[5, 41386, 47191]
[9, 42037, 47842]
[26, 43496, 49301]
[10, 45818, 51623]
[11, 47690, 53495]
[32, 49169, 54974]
[31, 51530, 57335]
[24, 53621, 59426]
[25, 55790, 61595]
[15, 57982, 63787]
[13, 59251, 65056]
[14, 60366, 66171]
[12, 61559, 67364]
[17, 62886, 68691]
[16, 64245, 70050]
[18, 65428, 71233]
[3, 66607, 72412]
[2, 2334, 8139]
[35, 2530, 8335]
[36, 4568, 10373]
[40, 6609, 12414]
[37, 10906, 16711]
[23, 13016, 18821]
[22, 15163, 20968]
[27, 17473, 23278]
[7, 20179, 25984]
[39, 22710, 28515]
[38, 27042, 32847]
[42, 29446, 35251]
[41, 33593, 39398]
[43, 37551, 43356]
[30, 42217, 48022]
[34, 44789, 50594]
[29, 46839, 52644]
[33, 49177, 54982]
[1, 57600, 57600]
I appreciate the response @Mizux - I'll continue to poke around and keep you in the loop. I tried my best to find this Discord you mentioned, but no dice; would you mind sharing that with me?
github.com/google/or-tools/blob/stable/README.md simply click on the "chat" button url should be discord.com/invite/ENkQrdf