A sequential order picking and loading system for outbound logistics operations

With short product life-cycles, frequent delivery schedules of products are demanded by customers. Efficient outbound logistics operations are key goals of companies wishing to maintain customer satisfaction and achieve competitive advantage. However, in current warehouse operations, order picking and loading are performed separately and products are picked manually from warehouses according to customer orders and stored temporarily in staging areas in order to fully utilize the capacity of carriers. In practice, the separation of order picking and the loading process usually results in problems of excess storage buffers, long operation time, and quality deterioration of sensitive products left in the staging area. In this paper, in order to tackle these problems, a sequential order picking and loading system (SOPLS) integrating order picking and loading processes is proposed. The Genetic Algorithm (GA) technique is adopted in the system to identify the optimum picking sequence of tours with minimal travel distance. In addition, parameter settings for GA generation are tested in the simulation to find the optimal solution. The validation of the feasibility of the proposed system is illustrated through a red wine storage scenario. By using the SOPLS in the case company, it is found that operation time for outbound logistics and product deterioration are greatly reduced.