Warehouse Picking Optimisation

A leading global e-commerce and online retailing company wanted to optimize their picking algorithm in order to reduce picking time and fatigue, and thereby speed up deliveries. Alumnus modified the standard TSP algorithm to run hierarchically and deal with picker-fatigue and stowing locations to reduce picking costs by 20-35%. 

Warehouse Picking Algorithm Optimization

​In modern warehouses, human or robotic pickers ‘pick up’ items from different shelves and place them into trolleys to be then taken for packaging. The shelves may be located at different heights, points and alleys of a warehouse. Some alleys may be narrow enough to allow trolleys to enter.

The cost of picking depends on the distance travelled within the warehouse and also on factors affecting productivity of picking staff due to fatigue of differing shelf-heights and stowing locations.

Taking the floor plan and picking order as input, our modified Hierarchical Traveling Salesman Problem algorithm optimised the picking route to minimise distance travelled and picker fatigue. Additional constraints of alley width and picker / trolley capacity were considered. The algorithm was also optimised to significantly reduce its running time.