Pick Path Optimization
What is pick path optimization?
Pick path optimization uses algorithms to determine the most efficient sequence and route for warehouse operatives to retrieve items.
What are the benefits of warehouse pick path optimization?
Pick path optimization minimizes the travel distance and time required to complete order fulfillment.
This improves productivity, reduces warehouse congestion and lowers the risk of tiredness and injury.
How picking route optimization works
Picking route optimization can be carried out using a warehouse management system (WMS).
The WMS evaluates all items in a pick assignment and calculates optimal collection sequences considering facility layout, aisle configurations and product locations.
Common pick path optimization strategies include:
S-shaped (or ‘serpentine) routing where operatives move down one aisle and back up the next
Return routing where operatives enter and exit from the same aisle end
Largest-gap routing where operatives skip aisles with no required picks
Zone-based optimization is also a solid strategy in large warehouses. This divides warehouses into districts, assigning operatives to specific areas where they develop location familiarity, reducing search time. The WMS coordinates handoffs between zones for multi-zone orders, balancing workload across areas while maintaining the efficiency gains from specialized picker assignments.
Dynamic path calculation adjusts routes in real time based on warehouse conditions. If congestion occurs in specific aisles or equipment failures block access, the system reroutes operatives around obstacles.
Optimal warehouse layout and picking route design
As well as identifying optimal routes for operatives to take, WMS can be used to devise an optimal warehouse layout.
Slotting optimization supports pick path efficiency and shortens pick paths by positioning fast-moving items in easily accessible locations near packing stations.
Pick density analysis identifies opportunities to consolidate product families or related items, reducing travel between picks. The WMS evaluates order patterns and identifies products frequently ordered together, then recommends slotting adjustments that place complementary items in proximity, shortening pick paths for common order profiles.
The WMS generates reports showing aisle utilization, congestion points and travel distance patterns, supporting decisions about aisle widths, rack configurations and cross-aisle placement that enhance overall picking efficiency.