发表机构
Swiss School of Business and Management, Geneva（瑞士商学院日内瓦校区）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究利用机器学习和深度学习方法，基于大量历史数据构建模型，以准确预测供应链系统中运输和物流的运输时间，从而提高物流一致性和绩效。
AI 中文摘要
本研究旨在利用机器学习和深度学习技术，寻找数据和方法，以准确预测供应链系统中运输和物流的预计运输时间。供应链生态系统非常复杂，严重依赖原材料和成品的运输与物流。准确的运输时间估计至关重要，因为它有助于供应链成员提高物流一致性和绩效，并有助于规划、需求预测、提前期管理和装配规划。客户交付侧的物流在客户满意度和客户之声中也起着关键作用。通过收集大量历史数据并采用新颖技术，本研究构建了一个准确的模型来预测库存的运输时间。
英文摘要
The purpose of this research is to find data and methods using machine learning and deep learning to correctly predict the estimated travel time for transportation and logistics in a supply chain system. The supply chain ecosystem is very complex and heavily relies on the transportation and logistics of raw materials and finished goods. Accurate travel time estimation is critical because it helps supply chain members to improve logistics consistency and performance. This helps in planning, demand forecasting, lead time management and assembly planning. The logistics on the delivery side of the customer also plays a crucial role in customer satisfaction and voice of customer. With the collection of huge historical data and using novel techniques, the research builds an accurate model to predict travel time of inventory.
Comments50 pages, 24 figures, 8 tables
