【主讲】辛林威，美国芝加哥大学Booth商学院助理教授
【主题】连续检查失销库存模型的1.79-近似算法
【时间】2020年4月15日（周三）上午 10:00am – 11:30am
【地点】线上：zoom软件，会议ID: 108 545 090
【语言】英文
【主办】管理科学与工程系
【简历】辛林威教授简历
辛林威博士是美国芝加哥大学Booth商学院助理教授（运营管理方向）。主要研究方向包括：库存管理，供应链管理，收益管理，不确定性优化，数据驱动的智能决策。他的学术研究获得过的荣誉包括：INFORMS应用概率学会颁发的最佳论文奖（2019），INFORMS George E. Nicholson最佳学生论文奖（2015），INFORMS最佳青年学者论文奖第二名（2015），INFORMS生产与服务运作管理最佳学生论文入围奖（2014），华人学者管理科学与工程协会颁发的最佳论文奖（2017）。他还获得过美国国家自然科学基金赞助的33万美元项目。他的研究成果发表在《Operations Research》，《Management Science》等学术期刊上。他曾经就职于沃尔玛全球电子商务研究中心及IBM Watson研究中心，与业界的研究合作包括：沃尔玛全球电子商务，阿里巴巴集团。
【Speaker】Linwei Xin, Assistant Professor, University of Chicago Booth School of Business.
【Topic】A 1.79-approximation algorithm for a continuous review lost-sales inventory model
【Time】Wednesday, April 15, 2020, 10:00am – 11:30am
【Venue】Online: zoom, Meeting ID: 108 545 090
【Language】English
【Organizer】Department of Management Science and Engineering
【Abstract】
Single-sourcing lost-sales inventory systems with lead times are notoriously difficult to optimize. Recent numerical experiments have suggested that a so-called capped base-stock policy demonstrates superior performance compared with existing heuristics. However, the superior performance lacks of a theoretical foundation (in the stochastic setting) and why such policies generally perform so well remains a major open question. In this paper, we provide a theoretical foundation for this phenomenon. In a continuous review lost-sales inventory model with lead times and Poisson demand, we prove that this policy has a worst-case performance guarantee of 1.79 by conducting an asymptotic analysis under large penalty cost and lead time following Reiman (2004). This result provides a deeper understanding of the superior numerical performance of capped base-stock policies, and presents a new approach to proving worst-case performance guarantees of simple policies in notoriously hard inventory problems. Finally, we will talk about the extension to a more complex dual-sourcing model.
