tsp.py

"""Simple Travelling Salesperson Problem (TSP) between cities."""

"""
setup
python -m pip install --upgrade --user ortools

from https://developers.google.com/optimization/install
and https://developers.google.com/optimization/routing/tsp
"""

from ortools.constraint_solver import routing_enums_pb2
from ortools.constraint_solver import pywrapcp


def read_data():
  import csv
  import numpy
  reader = csv.reader(open("full_matrix.csv", "r"), delimiter=",")
  x = list(reader)
  result = numpy.array(x).astype("int")
  return result

def create_data_model():
    """Stores the data for the problem."""
    data = {}
    data['distance_matrix'] = read_data()
    
    data['num_vehicles'] = 1
    data['depot'] = 1
    return data


def print_solution(manager, routing, solution):
    """Prints solution on console."""
    print('Objective: {} minutes'.format(solution.ObjectiveValue()))
    index = routing.Start(0)
    plan_output = 'Route for vehicle 0:\n'
    route_distance = 0
    while not routing.IsEnd(index):
        plan_output += ' {} ->'.format(manager.IndexToNode(index))
        previous_index = index
        index = solution.Value(routing.NextVar(index))
        route_distance += routing.GetArcCostForVehicle(previous_index, index, 0)
    plan_output += ' {}\n'.format(manager.IndexToNode(index))
    plan_output += 'Route time: {} minutes\n'.format(route_distance)
    print(plan_output)


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['distance_matrix']),
                                           data['num_vehicles'], data['depot'])

    # Create Routing Model.
    routing = pywrapcp.RoutingModel(manager)


    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 data['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)
    search_parameters.first_solution_strategy = (
        routing_enums_pb2.FirstSolutionStrategy.PATH_MOST_CONSTRAINED_ARC)

    # Solve the problem.
    solution = routing.SolveWithParameters(search_parameters)

    # Print solution on console.
    if solution:
        print_solution(manager, routing, solution)


if __name__ == '__main__':
    main()
    # print(read_data())