Supply Chain Logistics Optimization: Architecture Blueprint & Production Stack

from ortools.constraint_solver import routing_enums_pb2
from ortools.constraint_solver import pywrapcp
from typing import List, Dict, Any

def create_vrp_data_model() -> Dict[str, Any]:
    """Stores spatial distance matrix, vehicle capacities, and stop demands."""
    data = {}
    # 4x4 Distance Matrix (in meters) between Depot and Delivery Locations
    data['distance_matrix'] = [
        [0, 2450, 11700, 5800],
        [2450, 0, 9300, 3400],
        [11700, 9300, 0, 8500],
        [5800, 3400, 8500, 0]
    ]
    data['demands'] = [0, 15, 25, 10]          # Delivery package weights
    data['vehicle_capacities'] = [30, 30]       # Capacity per truck
    data['num_vehicles'] = 2
    data['depot'] = 0
    return data

def solve_vehicle_routing_problem():
    """Solves Capacitated Vehicle Routing Problem (CVRP) via Google OR-Tools."""
    data = create_vrp_data_model()
    
    # Create Routing Index Manager & Model
    manager = pywrapcp.RoutingIndexManager(
        len(data['distance_matrix']), data['num_vehicles'], data['depot']
    )
    routing = pywrapcp.RoutingModel(manager)

    # Define Distance Callback
    def distance_callback(from_index: int, to_index: int) -> int:
        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)

    # Add Capacity Constraints
    def demand_callback(from_index: int) -> int:
        from_node = manager.IndexToNode(from_index)
        return data['demands'][from_node]

    demand_callback_index = routing.RegisterUnaryTransitCallback(demand_callback)
    routing.AddDimensionWithVehicleCapacity(
        demand_callback_index, 0, data['vehicle_capacities'], True, 'Capacity'
    )

    # Search Parameters Configuration
    search_parameters = pywrapcp.DefaultRoutingSearchParameters()
    search_parameters.first_solution_strategy = (
        routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC
    )

    # Solve Optimization Problem
    solution = routing.SolveWithParameters(search_parameters)
    
    if solution:
        print("Vehicle Route Optimization Successful!")
        for vehicle_id in range(data['num_vehicles']):
            index = routing.Start(vehicle_id)
            plan_output = f"Route for Vehicle {vehicle_id}: "
            while not routing.IsEnd(index):
                plan_output += f"{manager.IndexToNode(index)} -> "
                index = solution.Value(routing.NextVar(index))
            plan_output += f"{manager.IndexToNode(index)}"
            print(plan_output)

if __name__ == '__main__':
    solve_vehicle_routing_problem()