关键词: 流利式货架, 分区拣选, 订单分批, 遗传算法, 储位指派

Abstract:

Based on the flow-rack zone order-picking system, it optimizes the flow-rack zone order-picking systems considering order batching methods and storage location assignment strategies. It considers reducing the residence time of the tasks and the waiting time of the pickers by reducing the working time differences between adjacent picking areas. A model is formulated whose objectives are minimizing the quantity of order batching and minimizing the sum of the differences of working time between any adjacent zones. And the model is solved by genetic algorithm to gain the order batching results and task release sequence. Considering storing the goods with higher turnover frequency into the layer of flow-rack where the items are the easiest to get, it proposes a classified random assignment strategy. The example shows that the results of the model perform well in the total completion time, total residence time, average fulfillment time and total waiting time compared to others. The classified random assignment strategy fundamentally reduces the picking time, which shortens the average fulfillment time and total completion time of the task, thereby improves the system efficiency and order response speed.

Key words: flow rack, zone order-picking, order batching, genetic algorithm, storage location assignment