An Improved MOEA/D for Order Scheduling Problem in Automated Warehouse

The order scheduling problem plays a significant role in the warehouse management for manufacturing corporations, and how to solve it efficiently will have direct impact on a company's strategy. In this paper, we take both the outbound orders and inbound orders into account, formulating the order scheduling problem as a constrained bi-objective optimization problem that minimizes both the total completion time and the maximum tardiness of outbound orders. A nearest-neighbor strategy is adopted to find a suitable storage location more efficiently when the storage/retrieve machine moves are executed as a dual command. We propose a modified multi-objective evolutionary algorithm based on decomposition, combined with shuffled frog leaping algorithm, to successfully solve the order scheduling problem. Our experimental results demonstrate the proposed algorithm is competitive compared with other multiobjective algorithms in solving order scheduling problem for automated warehouse system.