I’ve been experimenting with scaling last-mile routing problems beyond typical sizes (tens of thousands of stops).
Something interesting I ran into:
At some point, the bottleneck stops being the routing algorithm itself and becomes how the system is structured around it.
A few things that seemed to matter more than expected:
- clustering that accounts for constraints, not just geometry
- limiting route optimization cost as a bounded step
- handling inconsistencies at cluster boundaries
- avoiding recomputing distances repeatedly
What surprised me is that the system started showing close to linear scaling in practice, which is not what I expected given how these problems usually behave.
Curious if others have seen similar behavior when pushing VRP-type problems to larger scales, or if there are known approaches that deal with this differently.
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