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Machine Learning Warehouse Picking Optimisation

To optimise picking batches in a warehouse with up to 8,000 SKUs, we need to split picking orders into small segements of orders which would each fit into a plastic tote. The segments of orders can be grouped together to be picked in a single zone of a warehouse, with each order split across multiple warehouse zones.

Given a map of a warehouse, SKU data, location information and order data, split a batch of orders into the most optimal configuration, based on factors including tote utilisation and route optimisation.

The expected outcome is a Sagemaker (or equivalent) model, and an API gateway endpoint which will reply to REST queries to create picking batches.

Evner: Machine Learning (ML), AWS SageMaker, Algoritme

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Om arbejdsgiveren:
( 0 bedømmelser ) Adelaide, Australia

Projekt ID: #31922685

16 freelancere byder i gennemsnit $4484 timen for dette job

liveexperts123

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