Warehouse Batching: A Rule-Based and Algorithmic Perspective

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• Warehouse Batching A Rule-Based and Algorithmic
  Perspective

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• Introduction
• The increasing complexity of the e-commerce order
  mix has made order batching difficult.
• Picking constitutes a major warehouse process.
• It can improve the warehouses efficiency if done
  correctly.

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• This is Where Order Batching Comes In

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• The basic idea is to batch orders in such a way
  that the picking time is minimum.
• Reducing the trip distance for picking every item
  improves overall warehouse efficiency.
• While there are heuristic solutions that perform
  well, companys tend to shy away from them.

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• One problem is constructing a proper pipeline
  around the solution.
• Another is that while B2C orders can have
  similarities, B2B orders depend on the customer.
• This makes order batching difficult.

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• Our method uses past data to develop a
  rule-engine and pre-batch orders intelligently.
• These proto-batches are passed from our model to
  provide optimal batches for the picker.
• This significantly improves performance and
  avoids brittleness-inducing constraints.
• Small batches can be processed easily and
  efficiently by the model.

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• Conclusion
• We tested our approach to see if computing
  efficiency translates to operational efficiency.
• In multiple tests, it was found that the
  traversal distance was cut by half with our
  method.
• Our automated warehouse picking system reduces
  the complexity a picker has to deal with while
  picking items.

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• Hopstack
• Palo Alto, California
• Email Id contact_at_hopstack.io
• Website https//www.hopstack.io/
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  Algorithmic Perspective