A solution was developed to increase pick rate and reduce congestion for e-commerce order in a mixed -mode very narrow aisle warehouse.
The warehouse design and WMS configuration meant that picker wave were not being created and scheduled in a systematic manner. This was addressed through a custom order clustering function, developed in Python, and deployed as a serverless web service and integrated via a custom API.
Deliverables
- Real-time order clustering and pick path optimisation algorithm based on heuristic warehouse map
- Cloud based, on-demand deployment via serverless API
Key achievements
- E-commerce pick-rate increased by 60%
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