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Warehouses do order batching to save time while picking. However, the changing e-commerce industry has brought a mixture of different products making it difficult to batch orders efficiently. Hopstacku2019s algorithm helps in batching orders together more efficiently by using past order data and developing a rule engine. It can be beneficial for the warehouse and reduce the overall picking time by half.
 
                
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Warehouse Batching: A Rule-Based and Algorithmic Perspective
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.
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, company’s tend to shy away from them.
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.
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.
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.
Thank You !Would Love to Hear From You Hopstack Palo Alto, California Email Id: contact@hopstack.io Website: https://www.hopstack.io/ Know more- Warehouse Batching: A Rule-Based and Algorithmic Perspective