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1733. A scalable solution to joint routing and sorting problems
Invited abstract in session TD-57: Large-scale network optimization and inventory management, stream Optimization at Amazon.
Tuesday, 14:30-16:00Room: S06 (building: 101)
Authors (first author is the speaker)
| 1. | Charupriya Sharma
|
| Amazon | |
| 2. | George Iosifidis
|
| Amazon | |
| 3. | Daniel Guimarans
|
| Amazon | |
| 4. | Amit Kumar
|
| Amazon | |
| 5. | Georgios Paschos
|
| Amazon |
Abstract
We study the joint routing and sorting problem in Amazon’s middle mile network, which optimizes the routing of packages from fulfilment centers to delivery stations by using intermediate hubs to sort and consolidate flow. Packages are sorted into pallets, and packages in the same pallet are routed over the same path unless the pallet is dismantled in some intermediate hub. While the problem resembles a multi-commodity flow optimization problem, the operational constraints related to connectivity and sorting capacities and decisions create additional complications for routing that are not present in the literature.
We present a scalable, edge based model to solve this problem using a combination of search space reduction via edge pruning, a warm-start heuristic based on combinatorial optimization and a tight MIP formulation which uses a destination based aggregation of commodities. We observe significant improvements over path-based formulations in both run time and overall costs.
Keywords
- Transportation
- Combinatorial Optimization
- Network Design
Status: accepted
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