报告题目：Optimal Production Ramp-Up in the Smartphone Manufacturing Industry
报 告 人：邓天虎
报告时间：2019年9月18日，13:30—15:00
报告地点：博学楼I206
主办单位：现代供应链管理研究院
【报告人简介】
邓天虎，清华大学工业工程系副教授，国际运筹与管理科学学会Franz Edelman Laureates。2008年毕业于清华大学工业工程系，获学士学位；2013年毕业于美国加州大学伯克利分校，获博士学位。主要研究智慧供应链的方法论框架和企业解决方案。曾获中国运筹学会随机服务与运作管理分会优秀青年学者奖（2017）和北京市运筹学学会2016年青年优秀论文奖。负责执行的中石油天然气管网优化项目入围INFORMS设立的管理科学应用界最高奖项弗兰茨·厄德曼奖 （Franz Edelman Award）2018年决赛。目前研究成果已于Operations Research、Manufacturing & Service Operations Management, Informs Journal on Computing以及Interfaces等国际学术期刊上获得发表。学术兼职包括期刊Omega-the international Journal of management science的副主编。Production and Operations Management的客串副主编（guest Senior Editor）。任中国运筹学会随机服务与运作管理分会青年理事（2014年—至今）和中国运筹学会随机服务与运作管理分会青年理事（2014年—至今）。主持国家自然科学基金的优秀青年基金项目，参与完成国家重点自然科学基金1项。
【摘要】
Motivated by challenges in the smartphone manufacturing industry, we develop a dynamic production ramp-up model that can be applied to economically satisfy nonstationary demand for short-life-cycle products by high-tech companies. Due to shorter life cycles and more rapid evolution of smartphones, production ramp-up has been increasingly critical to the success of a new smartphone. In the production ramp-up, the key challenge is to match the increasing capacity to nonstationary demand. The high-tech smartphone manufacturers are urged to jointly consider the effect of increasing capacity and decreasing demand. We study the production planning problem using a high-dimensional Markov decision process (MDP) model to characterize the production ramp-up. To address the curse of dimensionality, we refine Monte Carlo tree search (MCTS) algorithm and theoretically analyze its convergence and computational complexity. In a real case study, we find that the MDP model achieves revenue improvement by stopping producing the existing product earlier than the benchmark policy. In synthetic instances, we validate that the proposed MCTS algorithm saves computation time without loss of solution quality compared with traditional value iteration algorithm. As part of the Lenovo production solution, our MDP model enables high-tech smartphone manufacturers to better plan the production ramp-up.
