Route & Logistics Optimizer

Plans who goes where, in what order, in which vehicle. From stops (lat/lng or a road distance matrix) and vehicles it returns each vehicle's ordered stops with arrival/leave times, km, load, Google Maps links and GeoJSON, respecting delivery time windows, capacity (weight and volume), shift times, max stops/km, skills, stops locked to a vehicle, open routes and mid-day re-planning. Also: savings vs the user's current plan, vs driver instinct and vs list order; stops that cannot be served with the reason; address sanity checks; optimal technician-to-job assignment (skills, jobs per person); and loading items into the fewest vehicles with the proven minimum. Benchmarked within ~1.3% of best-known on Solomon/Uchoa instances, optimal on TSPLIB tours tested. Decision cards first. Up to 300 stops; larger: route_optimizer_get_engine.

For more than 300 stops, or any order/stop file already in your code sandbox. Returns a complete numpy-only Python script with the same engine as route_optimizer; it reads the stop (and optional vehicle / item / worker / job) files, prints the decision cards and a line per vehicle, and writes the full plan to route_plan.json (and route_plan.geojson). Pass depot, time_limit_seconds and other inputs in params. No stop data reaches this server on this path.