时 间：2023年4月11日（星期二）上午9：00—12：00
地 点：电子科技大学清水河校区，经管楼C103
讲座一：On Deep Reinforcement Learning for OR/OM Problems （9：00-9：40）
主讲人：陈友华 教授
主持人：陈 旭 教授
主讲人简介：
陈友华教授现为香港城市大学商学院管理科学讲座教授。
他目前的研究兴趣包括医疗运营管理、物流供应链管理及机器学习在运营中的应用。他主持了一项关于 医疗管理的主题研究项目(Theme-based，两千万港元)，已于年前完成；现承担另一类似规模的应用项目，在香港推广一项新的养老模式。他的论文发表在运筹学、管理科学、POM和其他主流OR/MS期刊上，包括20多篇UTD文章。陈教授参与运营管理、供应链管理和物流管理的教学。清华大学工程本科，加拿大滑铁卢大学经济学硕士，多伦多大学管理学博士。加入城市大学之前，曾任教于新加坡国立大学(1997.7-2001.6)与香港中文大学(2001.7-2012.5)。
讲座简介：
Machine learning (ML) pervades a large number of academic disciplines and industries, and its impact is profound. Deep reinforcement learning (DRL) is an area of ML that focuses on sequential decision-making, which takes advantage of the deep artificial neural network architectures. In this talk I will first give a brief overview of the literature on DRL applications in operations research/management (OR/OM) problems. I then report my experience from a recent paper applying DRL to a data-driven multi-item inventory problem. Such a problem is notoriously difficult to optimize due to the curse of dimensionality, and direct use of DRL algorithm to solve it also results in poor performance. However, after incorporating an approximation into the standard DRL algorithm, the solution performance is significantly improved. The talk ends with insight sharing; in particular, views on the roles that OR/OM researchers can play, how our domain knowledge to be incorporated into DRL methods, and how to leverage DRL to solve large scale and complex OM/R problems, including combinatorial optimization problems arising from business/ management applications.
讲座二：Token-based Loyalty Program （9：45-10：25）
主讲人：杨 翼 教授
主持人：艾兴政 教授
主讲人简介：
杨翼，浙江大学管理学院副院长/太原理工大学副校长、
浙江大学长聘教授、求是特聘教授、博士生导师、数据驱动决策研究所所长、物流与决策优化研究所所长、国家杰出青年基金获得者、教育部青年长江学者、国家自然科学基金优秀青年科学基金获得者、运筹学会青年科技奖获得者。2011年毕业于香港中文大学系统工程与工程管理学系。主要研究方向包括供应链管理、运营管理、数据驱动决策。在高水平国际期刊上发表论文十余篇，特别是在 《Management Science》、《Operations Research》、《Manufacturing & Service Operations Management》、《Production and Operations Management》等UT/Dallas24种经济管理类国际公认顶级期刊上发表学术论文多篇。承担多项国家及省部级课题，现担任《Naval Research Logistics》、JORSC, APJOR的Associate Editor；《管理工程学报》领域编委、《运筹与管理》编委；担任运筹学会随机服务与运作管理分会理事、系统工程学会物流系统工程专业委员会理事、运筹学会智能工业数据解析与优化分会理事等工作。
茶歇时间：10：25-10：35
讲座三：Assortment and Pricing Management with Customer’s Product Unawareness（10：35-11：15）
主讲人：薛巍立 教授
主持人：潘景铭 教授
主讲人简介：
薛巍立，东南大学经济管理学院青年首席教授、博士生导师、副院长，
主要研究方向为品类与库存管理、数字化运营管理等，发表了包括Management Science、Operations Research、Production and Operations Management、Transportation Science等在内的国内外主流期刊论文近40篇；主持了包括国家自然科学基金优秀青年科学基金、国家自然科学基金重点项目在内的多项国家级和省部级项目；获得了江苏省哲学社会科学优秀成果奖等多个科研奖项。
讲座简介：
We develop a two-stage choice model with product unawareness and study assortment optimization and pricing problems under this choice model. Under the assumption that the utilities are independent and identically Gumbel-distributed, we derive a closed-form expression for the choice probabilities. For the assortment optimization problem, we find a revenue-ordered assortment is optimal for the niche product set but the assortment problem for the mainstream product set is NP-hard. Thus, we give a tight 1/2-approximation algorithm and devise a fully polynomial-time approximation scheme. For the joint assortment and pricing problem, we show that all products should be offered and the products in the same stage should be priced with the same revenue. We extend our analysis to the assortment optimization problem with mixed customers, advertisement costs and duopoly competition. The corresponding constant-factor algorithm or fully polynomial-time approximation scheme is provided. We also calibrate our choice model using a real data set on soft drinks and show that our model can outperform the standard MNL model in multiple criteria.
讲座四：A Double-edged Sword: New Technology Adoption for Primary Healthcare Delivery in China（11：20-12：00）
主讲人：朱 晗 教授
主持人：殷允强 教授
主讲人简介：
朱晗，教授、博士生导师，
现为东北财经大学管理科学与工程学院副院长（主管科研）、常任轨（tenure-track）教师，本科毕业于东北大学自动化专业，博士毕业于香港城市大学管理科学系，并于加拿大麦吉尔大学（McGill University）管理学院进行为期两年的博士后研究，从事运营管理相关的教学与科研工作。主持国家自然科学基金2项，在Operations Research, Manufacturing & Service Operations Management, Production and Operations Management顶级期刊和International Journal of Production Economics, International Journal of Production Research, Annals of Operations Research, Omega等权威期刊发表论文多篇，并入选辽宁省“百千万人才工程”，大连市高层次人才，大连市城市发展紧缺人才和辽宁省“兴辽英才计划”青年拔尖人才。
讲座简介：
In this work, we investigate how the primary healthcare delivery system (e.g., Family Doctor Contract Services in China) is impacted by new technologies such as wearable devices, which enable the subscribers’ effort to be observed by the clinic. We develop a co-production model that captures the complementarity of the clinic and subscribers’ efforts. We find that the adoption of new technology can lead to a win-win situation in which both the clinic and subscribers are better off and would like to exert more effort. Interestingly, we also find that when the subscribers’ output elasticity is relatively large, new technology adoption can result in a lose-lose situation in which the subscribers’ utility is reduced and the cost of the clinic is increased. As both the clinic and subscribers exert less effort in this situation, the subscribers are less likely to stay healthy, reducing social welfare. We also measure the value of the clinic’s commitment. Moreover, we develop a modified scheme that not only makes both the clinic and subscribers better off in the presence of new technology adoption, but also coordinates the co-production system such that social optimality is achieved. In addition, we also check the robustness of our model and results in the case with subscriber heterogeneity in the effort cost rate and inconvenience cost. Our results suggest that policymakers should be careful when considering new technology adoption, as it does not necessarily benefit both the clinic and subscribers.
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