How to use the ortools.constraint_solver.routing_enums_pb2 function in ortools

To help you get started, we’ve selected a few ortools examples, based on popular ways it is used in public projects.

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google / or-tools / ortools / constraint_solver / samples / tsp_distance_matrix.py View on Github

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.
    # [START arc_cost]
    routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
    # [END arc_cost]

    # Setting first solution heuristic.
    # [START parameters]
    search_parameters = pywrapcp.DefaultRoutingSearchParameters()
    search_parameters.first_solution_strategy = (
        routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)
    # [END parameters]

    # Solve the problem.
    # [START solve]
    assignment = routing.SolveWithParameters(search_parameters)
    # [END solve]

    # Print solution on console.
    # [START print_solution]
    if assignment:
        print_solution(manager, routing, assignment)
    # [END print_solution]

google / or-tools / ortools / constraint_solver / samples / simple_routing_program.py View on Github

to_node = int(manager.IndexToNode(to_index))
        return abs(to_node - from_node)

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

    # Define cost of each arc.
    # [START arc_cost]
    routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
    # [END arc_cost]

    # Setting first solution heuristic.
    # [START parameters]
    search_parameters = pywrapcp.DefaultRoutingSearchParameters()
    search_parameters.first_solution_strategy = (
        routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)  # pylint: disable=no-member
    # [END parameters]

    # Solve the problem.
    # [START solve]
    assignment = routing.SolveWithParameters(search_parameters)
    # [END solve]

    # Print solution on console.
    # [START print_solution]
    print('Objective: {}'.format(assignment.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

google / or-tools / ortools / constraint_solver / samples / tsp_cities.py View on Github

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.
    # [START arc_cost]
    routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
    # [END arc_cost]

    # Setting first solution heuristic.
    # [START parameters]
    search_parameters = pywrapcp.DefaultRoutingSearchParameters()
    search_parameters.first_solution_strategy = (
        routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)
    # [END parameters]

    # Solve the problem.
    # [START solve]
    assignment = routing.SolveWithParameters(search_parameters)
    # [END solve]

    # Print solution on console.
    # [START print_solution]
    if assignment:
        print_solution(manager, routing, assignment)
    # [END print_solution]

google / or-tools / ortools / constraint_solver / samples / vrp_pickup_delivery.py View on Github

pickup_index = manager.NodeToIndex(request[0])
        delivery_index = manager.NodeToIndex(request[1])
        routing.AddPickupAndDelivery(pickup_index, delivery_index)
        routing.solver().Add(
            routing.VehicleVar(pickup_index) == routing.VehicleVar(
                delivery_index))
        routing.solver().Add(
            distance_dimension.CumulVar(pickup_index) &lt;=
            distance_dimension.CumulVar(delivery_index))
    # [END pickup_delivery_constraint]

    # Setting first solution heuristic.
    # [START parameters]
    search_parameters = pywrapcp.DefaultRoutingSearchParameters()
    search_parameters.first_solution_strategy = (
        routing_enums_pb2.FirstSolutionStrategy.PARALLEL_CHEAPEST_INSERTION)
    # [END parameters]

    # Solve the problem.
    # [START solve]
    assignment = routing.SolveWithParameters(search_parameters)
    # [END solve]

    # Print solution on console.
    # [START print_solution]
    if assignment:
        print_solution(data, manager, routing, assignment)
    # [END print_solution]

google / or-tools / ortools / constraint_solver / doc / routing_svg.py View on Github

intervals.append(
                solver.FixedDurationIntervalVar(
                    time_dimension.CumulVar(routing.End(i)),
                    data.vehicle_unload_time, 'depot_interval '))

        depot_usage = [1 for i in range(data.num_vehicles * 2)]
        solver.AddConstraint(
            solver.Cumulative(intervals, depot_usage, data.depot_capacity,
                              'depot'))

    # Setting first solution heuristic (cheapest addition).
    search_parameters = pywrapcp.DefaultRoutingSearchParameters()
    # pylint: disable=no-member
    if not args['pickup_delivery']:
        search_parameters.first_solution_strategy = (
            routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)
    else:
        search_parameters.first_solution_strategy = (
            routing_enums_pb2.FirstSolutionStrategy.PARALLEL_CHEAPEST_INSERTION)

    # Solve the problem.
    assignment = routing.SolveWithParameters(search_parameters)
    # Print the solution.
    printer = SVGPrinter(args, data, manager, routing, assignment)
    printer.print_to_console()
    return 0

mricon / ingress-fieldplan / lib / maxfield.py View on Github

logger.debug('Capture cache miss, starting ortools calculation')

        manager = pywrapcp.RoutingIndexManager(a.order(), 1, [w_start], [linkplan[0][0]])
        routing = pywrapcp.RoutingModel(manager)

        def distance_callback(from_index, to_index):
            from_node = manager.IndexToNode(from_index)
            to_node = manager.IndexToNode(to_index)
            return get_portal_distance(from_node, to_node)

        transit_callback_index = routing.RegisterTransitCallback(distance_callback)
        routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)

        search_parameters = pywrapcp.DefaultRoutingSearchParameters()
        search_parameters.first_solution_strategy = (
            routing_enums_pb2.FirstSolutionStrategy.AUTOMATIC
        )
        logger.debug('Starting solver')
        assignment = routing.SolveWithParameters(search_parameters)
        logger.debug('Ended solver')

        if not assignment:
            logger.debug('Could not solve for these constraints, ignoring plan')
            capture_cache[cachekey] = None
            return None

        index = routing.Start(0)
        dist_ordered = list()
        while not routing.IsEnd(index):
            node = manager.IndexToNode(index)
            dist_ordered.append(node)
            index = assignment.Value(routing.NextVar(index))

How to use the ortools.constraint_solver.routing_enums_pb2 function in ortools

To help you get started, we’ve selected a few ortools examples, based on popular ways it is used in public projects.

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