examples/notebook/constraint_solver/tsp_circuit_board.ipynb
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First, you must install ortools package in this colab.
%pip install ortools
Simple Travelling Salesperson Problem (TSP) on a circuit board.
import math
from ortools.constraint_solver import routing_enums_pb2
from ortools.constraint_solver import pywrapcp
def create_data_model():
"""Stores the data for the problem."""
data = {}
# Locations in block units
data["locations"] = [
# fmt: off
(288, 149), (288, 129), (270, 133), (256, 141), (256, 157), (246, 157),
(236, 169), (228, 169), (228, 161), (220, 169), (212, 169), (204, 169),
(196, 169), (188, 169), (196, 161), (188, 145), (172, 145), (164, 145),
(156, 145), (148, 145), (140, 145), (148, 169), (164, 169), (172, 169),
(156, 169), (140, 169), (132, 169), (124, 169), (116, 161), (104, 153),
(104, 161), (104, 169), (90, 165), (80, 157), (64, 157), (64, 165),
(56, 169), (56, 161), (56, 153), (56, 145), (56, 137), (56, 129),
(56, 121), (40, 121), (40, 129), (40, 137), (40, 145), (40, 153),
(40, 161), (40, 169), (32, 169), (32, 161), (32, 153), (32, 145),
(32, 137), (32, 129), (32, 121), (32, 113), (40, 113), (56, 113),
(56, 105), (48, 99), (40, 99), (32, 97), (32, 89), (24, 89),
(16, 97), (16, 109), (8, 109), (8, 97), (8, 89), (8, 81),
(8, 73), (8, 65), (8, 57), (16, 57), (8, 49), (8, 41),
(24, 45), (32, 41), (32, 49), (32, 57), (32, 65), (32, 73),
(32, 81), (40, 83), (40, 73), (40, 63), (40, 51), (44, 43),
(44, 35), (44, 27), (32, 25), (24, 25), (16, 25), (16, 17),
(24, 17), (32, 17), (44, 11), (56, 9), (56, 17), (56, 25),
(56, 33), (56, 41), (64, 41), (72, 41), (72, 49), (56, 49),
(48, 51), (56, 57), (56, 65), (48, 63), (48, 73), (56, 73),
(56, 81), (48, 83), (56, 89), (56, 97), (104, 97), (104, 105),
(104, 113), (104, 121), (104, 129), (104, 137), (104, 145), (116, 145),
(124, 145), (132, 145), (132, 137), (140, 137), (148, 137), (156, 137),
(164, 137), (172, 125), (172, 117), (172, 109), (172, 101), (172, 93),
(172, 85), (180, 85), (180, 77), (180, 69), (180, 61), (180, 53),
(172, 53), (172, 61), (172, 69), (172, 77), (164, 81), (148, 85),
(124, 85), (124, 93), (124, 109), (124, 125), (124, 117), (124, 101),
(104, 89), (104, 81), (104, 73), (104, 65), (104, 49), (104, 41),
(104, 33), (104, 25), (104, 17), (92, 9), (80, 9), (72, 9),
(64, 21), (72, 25), (80, 25), (80, 25), (80, 41), (88, 49),
(104, 57), (124, 69), (124, 77), (132, 81), (140, 65), (132, 61),
(124, 61), (124, 53), (124, 45), (124, 37), (124, 29), (132, 21),
(124, 21), (120, 9), (128, 9), (136, 9), (148, 9), (162, 9),
(156, 25), (172, 21), (180, 21), (180, 29), (172, 29), (172, 37),
(172, 45), (180, 45), (180, 37), (188, 41), (196, 49), (204, 57),
(212, 65), (220, 73), (228, 69), (228, 77), (236, 77), (236, 69),
(236, 61), (228, 61), (228, 53), (236, 53), (236, 45), (228, 45),
(228, 37), (236, 37), (236, 29), (228, 29), (228, 21), (236, 21),
(252, 21), (260, 29), (260, 37), (260, 45), (260, 53), (260, 61),
(260, 69), (260, 77), (276, 77), (276, 69), (276, 61), (276, 53),
(284, 53), (284, 61), (284, 69), (284, 77), (284, 85), (284, 93),
(284, 101), (288, 109), (280, 109), (276, 101), (276, 93), (276, 85),
(268, 97), (260, 109), (252, 101), (260, 93), (260, 85), (236, 85),
(228, 85), (228, 93), (236, 93), (236, 101), (228, 101), (228, 109),
(228, 117), (228, 125), (220, 125), (212, 117), (204, 109), (196, 101),
(188, 93), (180, 93), (180, 101), (180, 109), (180, 117), (180, 125),
(196, 145), (204, 145), (212, 145), (220, 145), (228, 145), (236, 145),
(246, 141), (252, 125), (260, 129), (280, 133)
# fmt: on
]
data["num_vehicles"] = 1
data["depot"] = 0
return data
def compute_euclidean_distance_matrix(locations):
"""Creates callback to return distance between points."""
distances = {}
for from_counter, from_node in enumerate(locations):
distances[from_counter] = {}
for to_counter, to_node in enumerate(locations):
if from_counter == to_counter:
distances[from_counter][to_counter] = 0
else:
# Euclidean distance
distances[from_counter][to_counter] = int(
math.hypot((from_node[0] - to_node[0]), (from_node[1] - to_node[1]))
)
return distances
def print_solution(manager, routing, solution):
"""Prints solution on console."""
print(f"Objective: {solution.ObjectiveValue()}")
index = routing.Start(0)
plan_output = "Route:\n"
route_distance = 0
while not routing.IsEnd(index):
plan_output += f" {manager.IndexToNode(index)} ->"
previous_index = index
index = solution.Value(routing.NextVar(index))
route_distance += routing.GetArcCostForVehicle(previous_index, index, 0)
plan_output += f" {manager.IndexToNode(index)}\n"
print(plan_output)
plan_output += f"Objective: {route_distance}m\n"
def main():
"""Entry point of the program."""
# Instantiate the data problem.
data = create_data_model()
# Create the routing index manager.
manager = pywrapcp.RoutingIndexManager(
len(data["locations"]), data["num_vehicles"], data["depot"]
)
# Create Routing Model.
routing = pywrapcp.RoutingModel(manager)
distance_matrix = compute_euclidean_distance_matrix(data["locations"])
def distance_callback(from_index, to_index):
"""Returns the distance between the two nodes."""
# Convert from routing variable Index to distance matrix NodeIndex.
from_node = manager.IndexToNode(from_index)
to_node = manager.IndexToNode(to_index)
return distance_matrix[from_node][to_node]
transit_callback_index = routing.RegisterTransitCallback(distance_callback)
# Define cost of each arc.
routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
# Setting first solution heuristic.
search_parameters = pywrapcp.DefaultRoutingSearchParameters()
search_parameters.first_solution_strategy = (
routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC
)
# Solve the problem.
solution = routing.SolveWithParameters(search_parameters)
# Print solution on console.
if solution:
print_solution(manager, routing, solution)
main()