Dropping Nodes with Zero Demand

[Debom13]

Hi....I am working on a project which requires me to run the simulation of VRP for past three months. I have adjusted the code accordingly but the issue now is that vehicles are visiting the nodes which has zero demands as well. I want the vehicles to visit only the those nodes which has a valid demand. How can I do that?

[hklarner]

remove nodes with zero demands

[Mizux]

what about adding an AddDisjunction() with zero penalty ? i.e. solver will only visit it if it is along the way and won't impact the objective cost...

[Debom13]

can you please write the code?

[Debom13]

This is the code that I am using

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

def create_data_model(demand):
    """Stores the data for the problem."""
    data = {}
    data['distance_matrix'] = df.values
    data['demands'] = demand
    data['vehicle_capacities'] = [140, 140, 140, 140, 60]
    data['num_vehicles'] = 5
    data['depot'] = 0
    return data


def print_solution(data, manager, routing, solution):
    """Prints solution on console."""
    print(f'Objective: {solution.ObjectiveValue()}')
    total_distance = 0
    total_load = 0
    for vehicle_id in range(data['num_vehicles']):
        index = routing.Start(vehicle_id)
        plan_output = 'Route for vehicle {}:\n'.format(vehicle_id)
        route_distance = 0
        route_load = 0
        while not routing.IsEnd(index):
            node_index = manager.IndexToNode(index)
            route_load += data['demands'][node_index]
            plan_output += ' {0} Load({1}) -> '.format(node_index, route_load)
            previous_index = index
            index = solution.Value(routing.NextVar(index))
            route_distance += routing.GetArcCostForVehicle(
                previous_index, index, vehicle_id)
        plan_output += ' {0} Load({1})\n'.format(manager.IndexToNode(index),
                                                 route_load)
        plan_output += 'Distance of the route: {}m\n'.format(route_distance)
        plan_output += 'Load of the route: {}\n'.format(route_load)
        print(plan_output)
        total_distance += route_distance
        total_load += route_load
    print('Total distance of all routes: {}m'.format(total_distance))
    print('Total load of all routes: {}'.format(total_load))


def _main(demand):
    """Solve the CVRP problem."""
    # Instantiate the data problem.
    data = create_data_model(demand)

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

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

    # Create and register a 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)

    # Define cost of each arc.
    routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)


    # Add Capacity constraint.
    def demand_callback(from_index):
        """Returns the demand of the node."""
        # Convert from routing variable Index to demands NodeIndex.
        from_node = manager.IndexToNode(from_index)
        return data['demands'][from_node]

    demand_callback_index = routing.RegisterUnaryTransitCallback(
        demand_callback)
    routing.AddDimensionWithVehicleCapacity(
        demand_callback_index,
        0,  # null capacity slack
        data['vehicle_capacities'],  # vehicle maximum capacities
        True,  # start cumul to zero
        'Capacity')
    
    #vehicle distance travelled constraint
    distance_callback_index = routing.RegisterTransitCallback(distance_callback)
    dimension_name = 'Distance'
    routing.AddDimension(
        distance_callback_index,
        0,  # no slack
        80,  # vehicle maximum travel distance
        True,  # start cumul to zero
        dimension_name)
    distance_dimension = routing.GetDimensionOrDie(dimension_name)
    distance_dimension.SetGlobalSpanCostCoefficient(100)



    # Setting first solution heuristic.
    search_parameters = pywrapcp.DefaultRoutingSearchParameters()
    search_parameters.first_solution_strategy = (
        routing_enums_pb2.FirstSolutionStrategy.LOCAL_CHEAPEST_INSERTION)
    search_parameters.local_search_metaheuristic = (
        routing_enums_pb2.LocalSearchMetaheuristic.GREEDY_DESCENT)
    search_parameters.time_limit.FromSeconds(1)

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

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

def main():
  for col in df2.columns:
    if col != 'Location':
      demand = df2[col].values
      print(f"\n for Date {col} \n")
      _main(demand)
if __name__ == '__main__':
    main()

[Mizux]

should be something like that

for node in optional_node_list:
   index = manager.NodeToIndex(node)
   routing.AddDisjunction([index], 0)

[Debom13]

Solved. Thank you for the help.