Orders Group Problem In E-Fulfillment With Machine Learning: A Case Study At Nhat Tin Logistics

Abstract

Online shopping is significantly increasing at a high rate, especially after the SARS COVID pandemic. Nhat Tin Logistics has a fulfillment warehouse located in District 12, which is, processed to fulfill the goods to deliver them to customers. Nonetheless, the higher demand needs higher efficiency in the working process to minimize the cost and optimize performance in the business, especially in the Business-to-customer orde type. Machine Learning (ML) algorithm is applied to solve the Nhat Tin Logistics case study in terms of grouping orders. The results are then obtained using the Python programming language, and the best model to use to solve the problem is chosen by comparing the results for each type of cluster. The main objective of this study is to group orders to the picking and packing phases of the fulfillment process.