Perform slotting optimization by computing a velocity-based SKU-to-location assignment using historical pick frequency data from a WMS

Verified steps

1. Extract 90-day pick history from the WMS reporting API or database view: include SKU, pick location, pick quantity, and pick timestamp for all completed outbound orders
2. Compute a pick frequency score per SKU: total picks divided by active days; classify SKUs into velocity bands (A: top 20% of picks, B: next 30%, C: remaining 50%) using cumulative pick frequency thresholds
3. Map the warehouse floor plan to a travel-time matrix from the pick staging area to each storage location; use measured walking times or derive from aisle-bay coordinates and a fixed walking speed estimate
4. Score current slots by multiplying SKU velocity score by the travel-time from that location to staging; sum scores across all slots to obtain the current slotting efficiency index
5. Generate a candidate re-slot plan using a greedy assignment: sort A-velocity SKUs ascending by travel-time and assign them to the lowest travel-time available locations; repeat for B then C velocity bands
6. Submit slot change requests to the WMS slotting API one batch at a time, waiting for each relocation task to be confirmed complete before submitting the next to avoid dual-location conflicts during transition