The hard part of million-stop routing was not the route optimizer(github.com)
github.com
The hard part of million-stop routing was not the route optimizer
https://github.com/vizzito/last-mile-optimizer-paper
4 コメント
[deleted]
It's a different version, check it out
I’ve been working on a large-scale last-mile routing system and wrote a technical report about the architecture.
The main thing I found is that once the problem gets large enough, the bottleneck is not only route optimization. It becomes a systems problem: partitioning, boundary repair, graph reuse, bounded route-level optimization, and orchestration.
The report evaluates the system on the public Amazon Last Mile Routing Research Challenge dataset using a shared external OSRM/Google measurement protocol. It does not claim to reproduce Amazon’s internal routing objective.
Main results: - 23.3% less measured distance under the external protocol - 11.1% fewer routes - 1M stops processed in ~20 minutes on commodity hardware
I’d be interested in feedback from people who have worked on routing, optimization, dispatch systems, logistics, or large-scale scheduling. What would you expect to see in the evaluation to make this more convincing?
Thanks!
The main thing I found is that once the problem gets large enough, the bottleneck is not only route optimization. It becomes a systems problem: partitioning, boundary repair, graph reuse, bounded route-level optimization, and orchestration.
The report evaluates the system on the public Amazon Last Mile Routing Research Challenge dataset using a shared external OSRM/Google measurement protocol. It does not claim to reproduce Amazon’s internal routing objective.
Main results: - 23.3% less measured distance under the external protocol - 11.1% fewer routes - 1M stops processed in ~20 minutes on commodity hardware
I’d be interested in feedback from people who have worked on routing, optimization, dispatch systems, logistics, or large-scale scheduling. What would you expect to see in the evaluation to make this more convincing?
Thanks!
(28 days ago) https://news.ycombinator.com/item?id=47581180