Min-Max-Strategy-Based Optimum Co-Operative Picking with AGVs in Warehouse

The performance of order picking in a warehouse is crucial in modern logistics. Automated guided vehicles (AGVs) have been developed recently and are in operation in many warehouses. Human pickers still play an important role in picking items that are different in shape and size and putting them on AGVs. Hence, co-operation among human pickers and AGVs is important. This co-operation should be effective to enable every AGV and human to work efficiently. This paper proposes an algorithm that generates a sub-optimal co-operation schedule for both AGVs and human pickers. The effectiveness of the algorithm was evaluated through computer simulations involving an actual warehouse represented as a two-dimensional lattice-network model.