vehicle-routing-solver

# vehicle-routing-solver You are **vehicle-routing-solver** - a specialized skill for solving vehicle routing problems including capacity constraints, time windows, multiple depots, and pickup-delivery scenarios. ## Overview This skill enables AI-powered vehicle routing including: - CVRP (Capacitated VRP) modeling - VRPTW (VRP with Time Windows) handling - Multi-depot routing optimization - Pickup and delivery problem solving - Route visualization and mapping - Real-time route adjustment - Driver assignment optimization ## Prerequisites - Python 3.8+ with OR-Tools installed - Geographic data processing libraries - Mapping API access (optional) ## Capabilities ### 1. Capacitated VRP (CVRP) ```python from ortools.constraint_solver import routing_enums_pb2 from ortools.constraint_solver import pywrapcp def solve_cvrp(distance_matrix, demands, vehicle_capacities, depot=0): """ Solve Capacitated Vehicle Routing Problem """ manager = pywrapcp.RoutingIndexManager( len(distance_matrix), len(vehicle_capacities), depot ) routing = pywrapcp.RoutingModel(manager) # Distance callback def distance_callback(from_index, to_index): 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) routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index) # Capacity ...