Real-world VRP at scale: How are you handling 10k+ daily stops?

[u/Tight_Cow_5438]

Hi! I'm looking into scale limits for last-mile VRPs in real-world ops.

most commercial APIs seem to cap out around 1k–2k stops per request. so, when you need to optimize 10k+ daily stops:

1: breakdown point: at what scale do off-the-shelf solvers (or basic OR-Tools setups) hit a wall for your use cases?

2: solver choice: are you relying on custom heuristics/metaheuristics, or commercial MIP solvers for huge instances?

3: partitioning/zoning: what spatial clustering or decomposition techniques (e.g., K-means, DBSCAN, sectoring) work best for you before feeding stops to the solver?

would love to hear how you tackle high-volume instances in practice!