Hey Santa, I've been crunching numbers on your delivery routes and think there's a way to cut your journey time—interested in a quick algorithm rundown?

Use a weighted graph of stops, run Dijkstra from the depot each night; add a penalty for routes that intersect previously visited paths that night to avoid overlap, and schedule stops in batches so each truck does a closed loop that ends back at the depot. That reduces idle time and guarantees a 12‑hour maximum.

Here’s a minimal sketch in Python – no GUI, just raw data. ```python # nodes are stops, 0 is the depot edges = { 0: [(1,2),(2,4),(3,7)], 1: [(0,2),(2,1),(4,5)], 2: [(0,4),(1,1),(3,3),(4,2)], 3: [(0,7),(2,3),(4,6)], 4: [(1,5),(2,2),(3,6),(0,8)] } def dijkstra(start): import heapq dist = {n: float('inf') for n in edges} dist[start] = 0 pq = [(0,start)] while pq: d,u = heapq.heappop(pq) if d!=dist[u]: continue for v,w in edges[u]: if d+w < dist[v]: dist[v] = d+w heapq.heappush(pq,(dist[v],v)) return dist # get shortest round‑trip from depot dist = dijkstra(0) route = sorted(dist.items(), key=lambda x: x[1]) # just a naive batch print(route) ``` Run it, tweak the weights, and you get a quick list of where each truck should go. Remember to add a small penalty for overlapping edges if you want to keep routes separate. That’s it, no fancy GUI needed.