How to use the ortools.constraint_solver.pywrapcp.RoutingModel function in ortools

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github google / or-tools / ortools / constraint_solver / samples / vrpgs.py View on Github external
def main():
    """Entry point of the program"""
    # Instantiate the data problem.
    data = create_data_model()

    # Create the routing index manager
    manager = pywrapcp.RoutingIndexManager(data['num_locations'],
                                           data['num_vehicles'], data['depot'])

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

    # Define weight of each edge
    distance_evaluator_index = routing.RegisterTransitCallback(
        partial(create_distance_evaluator(data), manager))
    routing.SetArcCostEvaluatorOfAllVehicles(distance_evaluator_index)
    add_distance_dimension(routing, distance_evaluator_index)

    # Setting first solution heuristic (cheapest addition).
    search_parameters = pywrapcp.DefaultRoutingSearchParameters()
    search_parameters.first_solution_strategy = (
        routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)  # pylint: disable=no-member
    # Solve the problem.
    assignment = routing.SolveWithParameters(search_parameters)
    print_solution(data, routing, manager, assignment)
github google / or-tools / ortools / constraint_solver / samples / vrp_time_windows.py View on Github external
def main():
    """Solve the VRP with time windows."""
    # Instantiate the data problem.
    # [START data]
    data = create_data_model()
    # [END data]

    # Create the routing index manager.
    # [START index_manager]
    manager = pywrapcp.RoutingIndexManager(len(data['time_matrix']),
                                           data['num_vehicles'], data['depot'])
    # [END index_manager]

    # Create Routing Model.
    # [START routing_model]
    routing = pywrapcp.RoutingModel(manager)

    # [END routing_model]

    # Create and register a transit callback.
    # [START transit_callback]
    def time_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)
        return data['time_matrix'][from_node][to_node]

    transit_callback_index = routing.RegisterTransitCallback(time_callback)
    # [END transit_callback]

    # Define cost of each arc.
github google / or-tools / ortools / constraint_solver / samples / vrp_resources.py View on Github external
def main():
    """Solve the VRP with time windows."""
    # Instantiate the data problem.
    # [START data]
    data = create_data_model()
    # [END data]

    # Create the routing index manager.
    # [START index_manager]
    manager = pywrapcp.RoutingIndexManager(len(data['time_matrix']),
                                           data['num_vehicles'], data['depot'])
    # [END index_manager]

    # Create Routing Model.
    # [START routing_model]
    routing = pywrapcp.RoutingModel(manager)

    # [END routing_model]

    # Create and register a transit callback.
    # [START transit_callback]
    def time_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)
        return data['time_matrix'][from_node][to_node]

    transit_callback_index = routing.RegisterTransitCallback(time_callback)
    # [END transit_callback]

    # Define cost of each arc.
github google / or-tools / ortools / constraint_solver / samples / vrp_with_time_limit.py View on Github external
# Instantiate the data problem.
    # [START data]
    num_locations = 20;
    num_vehicles = 5;
    depot = 0;
    # [END data]

    # Create the routing index manager.
    # [START index_manager]
    manager = pywrapcp.RoutingIndexManager(
        num_locations, num_vehicles, depot)
    # [END index_manager]

    # Create Routing Model.
    # [START routing_model]
    routing = pywrapcp.RoutingModel(manager)

    # [END routing_model]

    # Create and register a transit callback.
    # [START transit_callback]
    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 1

    transit_callback_index = routing.RegisterTransitCallback(distance_callback)
    # [END transit_callback]

    # Define cost of each arc.
github google / or-tools / ortools / constraint_solver / samples / vrp_pickup_delivery.py View on Github external
def main():
    """Entry point of the program."""
    # Instantiate the data problem.
    # [START data]
    data = create_data_model()
    # [END data]

    # Create the routing index manager.
    # [START index_manager]
    manager = pywrapcp.RoutingIndexManager(len(data['distance_matrix']),
                                           data['num_vehicles'], data['depot'])
    # [END index_manager]

    # Create Routing Model.
    # [START routing_model]
    routing = pywrapcp.RoutingModel(manager)

    # [END routing_model]

    # Define cost of each arc.
    # [START arc_cost]
    def distance_callback(from_index, to_index):
        """Returns the manhattan 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)
    routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
    # [END arc_cost]
github Map-A-Droid / MAD / mapadroid / route / routecalc / calculate_route_all.py View on Github external
def route_calc_ortools(lessCoordinates, route_name):
    route_logger = get_origin_logger(logger, origin=route_name)
    data = create_data_model(lessCoordinates)

    # 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.
github google / or-tools / ortools / constraint_solver / samples / vrp.py View on Github external
def main():
    """Entry point of the program."""
    # Instantiate the data problem.
    # [START data]
    data = create_data_model()
    # [END data]

    # Create the routing index manager.
    # [START index_manager]
    manager = pywrapcp.RoutingIndexManager(len(data['distance_matrix']),
                                           data['num_vehicles'], data['depot'])
    # [END index_manager]

    # Create Routing Model.
    # [START routing_model]
    routing = pywrapcp.RoutingModel(manager)

    # [END routing_model]

    # Create and register a transit callback.
    # [START transit_callback]
    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)
    # [END transit_callback]

    # Define cost of each arc.
github tanmoyie / Operations-Research / Travelling Salesman Problem / traveling_salesman_problem(finding_travelling_path_covering_all_points_with_min_total_distance).py View on Github external
def main():
  # The order of the cities in the array is the following:
  # Cities
  city_names = ["Dhaka", "Syhlet", "Chittagonj", "Rajshahi", "Jossore", "Dinajpur", "Coxsbazar", "Narsingdi"]
  tsp_size = len(city_names)
  num_routes = 1    # The number of routes, which is 1 in the TSP.
  # Nodes are indexed from 0 to tsp_size - 1. The depot is the starting node of the route.
  depot = 0

  # Create routing model
  if tsp_size > 0:
    routing = pywrapcp.RoutingModel(tsp_size, num_routes, depot)
    search_parameters = pywrapcp.RoutingModel.DefaultSearchParameters()

    # Create the distance callback, which takes two arguments (the from and to node indices)
    # and returns the distance between these nodes.
    dist_between_nodes = CreateDistanceCallback()
    dist_callback = dist_between_nodes.Distance
    routing.SetArcCostEvaluatorOfAllVehicles(dist_callback)
    # Solve, returns a solution if any.
    assignment = routing.SolveWithParameters(search_parameters)
    if assignment:
      # Solution cost.
      print ("Total distance: " + str(assignment.ObjectiveValue()) + " miles\n")
      # Inspect solution.
      # Only one route here; otherwise iterate from 0 to routing.vehicles() - 1
      route_number = 0
      index = routing.Start(route_number) # Index of the variable for the starting node.
      route = ''
github google / or-tools / ortools / constraint_solver / samples / tsp_circuit_board.py View on Github external
def main():
    """Entry point of the program."""
    # Instantiate the data problem.
    # [START data]
    data = create_data_model()
    # [END data]

    # Create the routing index manager.
    # [START index_manager]
    manager = pywrapcp.RoutingIndexManager(len(data['locations']),
                                           data['num_vehicles'], data['depot'])
    # [END index_manager]

    # Create Routing Model.
    # [START routing_model]
    routing = pywrapcp.RoutingModel(manager)
    # [END routing_model]

    # [START transit_callback]
    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)
    # [END transit_callback]

    # Define cost of each arc.