工商管理学院建院30周年
系列学术报告 第22场
课程题目：
Methods in OM:
Stochastic dynamic programming, data mining and machine learning
——A brief introduction
主讲人：Dong-Ping Song 教授
时间：2024年7月28日-7月30日 每晚8:00
主持人：蒋忠中、郑伟
地点：ZOOM
https://liverpool-ac-uk.zoom.us/j/92938046257?pwd=3H8YNH7a9BTlhPHhMu1ntOeZ6O1cNF.1
无需注册，可直接点击链接入会。
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会议号: 929 3804 6257
密码: .%0AFDkQ
课程摘要：
Talk1: My publication and editorial experience（7月28日）
Summary: In this talk, I will start with a brief review of my publication experience and recent research grants, then explain the general paper review process. The focus of the talk is to share my editorial experience of TRE including how to avoid desk rejection and the full review process. I will also explain the paper evaluation criteria in the UK REF system.
Talk2: Container shipping supply chain: overview, management, and opportunities（7月28日）
Summary: In this talk, I will explain the importance of container shipping industry and its development. The key players, logistics flows and their relationships will be discussed. Five logistics segments within container shipping supply chain will be explained. The main management problems and potential research opportunities will be discussed in each individual logistics segment.
Talk3: Stochastic dynamic programming: introduction and applications in container management（7月29日）
Summary: Manufacturing production system and supply chain systems are often characterised by dynamic operations and uncertainty. This implies that we are required to make sequential decisions over time in anticipation of the impact of future unpredictable factors. Treating the uncertainty as stochasticity using random variables over time, optimal sequential decision-making problems can be tackled using a stochastic dynamic programming approach. In this session, I will introduce the stochastic dynamic programming technique, including the basic knowledge and its applications in container management problems.
Talk4: Data mining & machine learning: introduction and application in port management（7月30日）
Summary: In this talk, I will introduce the concepts of data mining and machine learning for business management. The CRISP-DM Process Model will be explained. Various data mining and machine learning methods will be introduced with the focus on classification methods and decision tree-based classification. Finally, the application of classification predictive analytics to container port operation management will be reported.
主讲人简介：
Dr. Song is a professor at Liverpool University Management School. He has developed research expertise in applying data analytics, mathematical modelling, artificial intelligence, and simulation-based tools to various supply chain, logistics and transportation systems, particularly in the area of maritime transport. He has managed several research projects funded by EPSRC, ESRC, Royal Society, British Council, Innovation Launchpad Network+, European Commission, and Chinese Research Councils. The goal is to advance the knowledge and assist industries to improve management considering economic, environmental and societal performance. Now, he is a senior Member of IEEE and associate editor of Transportation Research Part E: Logistics and Transportation Review.
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