| dc.description.abstract | Nowadays, online shopping has rapidly developed, and the ＂Stay-at-Home Economy＂ has accelerated the alteration of consumer behavior from the retailer to e-commerce platforms. Due to this situation, the change of shopping mode has increased the difficulty of logistics. The 24-hour fast delivery and the increasing volume of online shopping test the logistic efficiency. Response instantly 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 takes 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 conducts one order at a time. The advantage of this method is simple to complete for those manipulators, 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 be operated by pickers together, so a picker can select multiple and similar orders at the same time, reducing the picking time. The pros and cons of order batching impacts significantly.
However, in past essay about order batching, the research environment was relatively single and seldom discussed ＂zone picking system＂. This kind of picking system has a prime merit, smooth picking routes, but the disadvantage is that the picking traffic flow is much more complicated. It is important to match an excellent picking strategy. Based on the reasons above, this research will study the picking strategy in zone picking system, and will mainly discourse the order batching problem. In addition, in order to improve the efficiency, this research will also state the order batch selection problem and dynamic order picking routing problem, and finally find the most suitable picking strategy. Expecting that through this complete simulation experiments and statistical analysis can increase the understanding of order picking issues for the future of distribution center. | en_US |