VRP with Collects and Deliveries

vrp_collect_deliveries.py

#!/usr/bin/env python3
"""Capacitated Vehicle Routing Problem (CVRP)."""

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

###########################
# Problem Data Definition #
###########################
def create_data_model():
    """Stores the data for the problem"""
    data = {}
    data['demands'] = \
          [0, # depot
           15, # Pickup
           -13, # Delivery
           -20, # Delivery
           10, # Pickup
           15] # Pickup
    data['num_vehicles'] = 3
    data['vehicle_capacities'] = [30, 20, 30]
    data['depot'] = 0
    return data

###########
# Printer #
###########
def print_solution(data, manager, routing, solution):  # pylint:disable=too-many-locals
    """Prints solution on console"""
    print('Objective: {}'.format(solution.ObjectiveValue()))
    total_distance = 0
    delivery_dimension = routing.GetDimensionOrDie('Delivery')
    load_dimension = routing.GetDimensionOrDie('Load')
    for vehicle_id in range(manager.GetNumberOfVehicles()):
        index = routing.Start(vehicle_id)
        plan_output = 'Route for vehicle {}:\n'.format(vehicle_id)
        distance = 0
        while not routing.IsEnd(index):
            delivery_var = delivery_dimension.CumulVar(index)
            load_var = load_dimension.CumulVar(index)
            plan_output += f' {manager.IndexToNode(index)} Delivery({solution.Value(delivery_var)}) Load({solution.Value(load_var)}) -> '
            previous_index = index
            index = solution.Value(routing.NextVar(index))
            distance += routing.GetArcCostForVehicle(previous_index, index, vehicle_id)
        delivery_var = delivery_dimension.CumulVar(index)
        load_var = load_dimension.CumulVar(index)
        plan_output += f' {manager.IndexToNode(index)} Delivery({solution.Value(delivery_var)}) Load({solution.Value(load_var)})\n'
        plan_output += 'Distance of the route: {}m\n'.format(distance)
        print(plan_output)
        total_distance += distance
    print('Total Distance of all routes: {}m'.format(total_distance))


########
# Main #
########
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['demands']),
            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 10

    transit_callback_index = routing.RegisterTransitCallback(distance_callback)

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

    # Add Delivery dimension.
    def delivery_callback(from_index):
        """Returns the delivery of the node."""
        # Convert from routing variable Index to demands NodeIndex.
        from_node = manager.IndexToNode(from_index)
        value = data['demands'][from_node]
        return value if value < 0 else 0

    delivery_callback_index = routing.RegisterUnaryTransitCallback(delivery_callback)
    routing.AddDimensionWithVehicleCapacity(
        delivery_callback_index,
        0,  # null capacity slack
        data['vehicle_capacities'],  # vehicle maximum capacities
        False,  # don't start cumul to zero
        'Delivery')

    # Add Load dimension.
    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
        False,  # don't start cumul to zero
        'Load')

    # Force both dimension to start in sync
    delivery_dimension = routing.GetDimensionOrDie('Delivery')
    load_dimension = routing.GetDimensionOrDie('Load')
    for vehicle_id in range(manager.GetNumberOfVehicles()):
        index = routing.Start(vehicle_id)
        routing.solver().Add(delivery_dimension.CumulVar(index) == load_dimension.CumulVar(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
    search_parameters.local_search_metaheuristic = (
        routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH)
    search_parameters.time_limit.FromSeconds(1)

    # Solve the problem.
    solution = routing.SolveWithParameters(search_parameters)
    print_solution(data, manager, routing, solution)


if __name__ == '__main__':
    main()

zz_readme.md

possible output:

[0]─[~/work/tmp]
[^v^]─mizux@nuc10i7 %./vrp_collect_deliveries.py
Objective: 70
Route for vehicle 0:
 0 Delivery(0) Load(0) ->  0 Delivery(0) Load(0)
Distance of the route: 0m

Route for vehicle 1:
 0 Delivery(20) Load(20) ->  3 Delivery(20) Load(20) ->  1 Delivery(0) Load(0) ->  0 Delivery(0) Load(15)
Distance of the route: 30m

Route for vehicle 2:
 0 Delivery(13) Load(13) ->  2 Delivery(13) Load(13) ->  5 Delivery(0) Load(0) ->  4 Delivery(0) Load(15) ->  0 Delivery(0) Load(25)
Distance of the route: 40m

Total Distance of all routes: 70m