dc.description.abstract | In recent years, the prosperous development of the Internet has led to the rise of the e-commerce market. It has become more common for consumers to shop online, and competition among e-commerce companies has become increasingly fierce. Research indicates that there are many factors for the success of e-commerce, one of which is complete logistics services. Consumers’ satisfaction with the logistics services provided by virtual shop will finally affect their operational performance. Without good logistics services, the deadline for the delivery of products to consumers is greatly delayed, and online e-commerce companies cannot earn recognition for consumers. Doing a good job in logistics effectively reduces operating costs, satisfies customer requirements, and improves customer service levels. It is the key element for the sustainable operation of enterprises in modern society.
However, among the various internal operations of the Distribution Centre, picking operation is a labor-intensive and cost-intensive activity. The time of picking operation accounts for about 30-40% of the overall logistics operation time. In terms of cost, the labor cost of picking accounts for 15-20% of the total cost of the Distribution Centre, while the picking operations of the Distribution Centre account for about 55% of the total cost of operations. Therefore, having a complete picking operation process will have a decisive impact on the improvement of the overall operational efficiency of the Distribution Centre.
This research mainly discusses the method of order batching operations in Distribution Centre. Based on four picking policies, different order similarity coefficients are proposed, and clustering method is used for order batching. Use the Total Travel Distance of Pickers(TTD)to evaluate the performance of order batching methods under different picking policies. In addition, this research will compare with the order batching method proposed by previous researches, and put forward suggestions for future research methods, for the Distribution Centre’s picking reference basis. It is also expected to be practically applied to the real-life warehousing environment to improve the efficiency of picking operations. | en_US |