Shortest-Route Delivery Optimizer

Overview

Most small fleets and field-service teams plan routes by experience — a dispatcher who knows the area orders the stops manually. That works until the stop count grows or the dispatcher is out. This tool takes a list of stops and returns the shortest viable route, accounting for real traffic conditions, time windows, and vehicle constraints.

The problem

Manual route planning doesn’t scale past a handful of stops, and it doesn’t account for live traffic. A route that looked efficient on a map can lose an hour to congestion that a static plan never saw coming.

What it does

• Takes a daily stop list (addresses, time windows, priority) and computes an optimized multi-stop route using the Google Routes API
• Recalculates automatically when traffic conditions shift or a stop is added mid-day
• Respects hard constraints — delivery windows, vehicle capacity, driver shift length
• Outputs turn-by-turn routes to drivers’ phones and a summary (total miles, estimated drive time, stop sequence) to the dispatcher

Stack

A Python service handles the route-optimization logic and constraint solving, calling the Google Routes API for live traffic-aware distance and duration data. n8n schedules the daily route generation and pushes results to drivers via SMS/app notification and to dispatch via a simple dashboard.

Why it matters

Route efficiency compounds — a 10-15% reduction in drive time across a fleet, every day, adds up to real fuel and labor savings without buying a single new vehicle.