Research And Application Of Optimized Order Batching Method Based On Picking And Sorting Time

Nowadays, with the rapid development of E-commerce, Customer orders are becoming dispersed, numerous and diverse, which demands more of distribution center's response time and service quality. In labor-intensive distribution center, the human resources related to picking work accounts for about 50%, and the order picking time accounts for about 30%-40% of the distribution center's whole operation time. Picking-by-order has been unable to satisfy the needs to operate efficiently of the distribution center, while order batching strategy can put many small orders together for batch processing, which can largely improve the picking efficiency of distribution center.Traditional order batching research only considered the influence of the batching results on travel time, but ignored the time of order sorting following order batching procedure. In fact, the smaller the batch number of a set of orders is, which means assigning as more orders to a batch as possible, the less the travel time is theoretically. However, the sorting time becomes longer due to the increase number of orders forming a batch. Therefore, this paper fully considers the influence of order batching results to both travel time and sorting time, and gives a mathematical model of the order batching problem, the objective of this model is to minimize the sum of travel time and sorting time. Besides, the genetic algorithm will be used for the batching model to seek the best way of grouping orders into batches.Taking the sum of travel time and sorting time as the optimization objective, this paper conducts several simulation experiments of the batching model and its algorithm, and analyze the impact of order numbers, batch capacity and other parameters to the optimization objective. They all prove that the batching model and the genetic algorithm can solve batching problems effectively and stably. Finally, the batching method is applied in the order picking system to optimize the order picking process, which reduces the order processing time and increase the picking efficiency of distribution center.