That’s not really how Uber eats or similar apps work. Drivers are very rarely on more than 1 delivery at a time.
And again, until our problem size grows to a point where we cannot solve it in polynomial time, it is in P by definition.
Traveling salesman starts to evade computational time at around 20 to 30 nodes.
So because of this, as I said before, it employs a greedy heuristic to make light work on decent guesses for the problem, knowing the problem size will never get out of scope, so doing so is relatively safe.
You’re right that in theory multiple deliveries look like a tiny version of TSP, but in practice it’s nowhere near the scale that makes TSP an NP problem.
Nemo@slrpnk.net 1 day ago
Finding the best route is NP-complete. Finding a route is trivial. Finding a pretty good route is good enough for their purposes.
Also keep in mind they’re not to much trying up find the best route between static stops as trying to minimize time between pickup and dropoff for a list of (origin, destination) pairs, constrained by staggered start times for the pickup origins. It’s fundamentally a different problem.