| dc.description.abstract | In recent years, online shopping has developed rapidly, and the ＂Stay-at-Home Economy＂ has prompted the shift of consumer channels from the retailer to e-commerce platforms. Changes in shopping patterns have also increased the difficulty of logistics. The 24-hour fast delivery and increasing delivery volume of online shopping test the logistic efficiency. Quick response to consumer needs is a necessary ability to distribution centers.
Among all operation of the distribution center, order picking is the most workload and manpower operation. At present, most distribution centers are ＂labor-intensive＂ industry. Order picking account for about 50-75% of the total operating costs, and the order picking time is about 30-40% of the total operating time. Therefore, how to optimize the order picking process is the primary goal of the distribution center.
In the past, the general order picking method was ＂individual picking＂, that is, one picker picks one order at a time. The advantage of this method is that it is very simple, but the disadvantage is that it is less efficient. In this regard, the common solution is ＂batch picking＂, which means that similar orders are merged to same order batch and opereted together, so a picker can pick multiple similar orders at the same time, reducing the picking time. The pros and cons of order batching have a key impact on batch picking.
However, in the past literature on order batching, the research environment was relatively single and seldom discussed the ＂zone picking system＂. This picking system has the advantages of a smooth picking route, but the disadvantage is that the picking traffic flow is complicated, and it is important to match an excellent picking strategy. Based on the above reasons, this research will study the picking strategy in the zone picking system, and mainly discuss the order batching problem. In addition, in order to further improve the efficiency, this research also discusses the order batch selection problem and dynamic order picking routing problem, and find the most suitable picking strategy. It is hoped that through complete simulation experiments and statistical analysis, it will increase the understanding of order picking issues. | en_US |