性爱网站

时间：2025年6月10日 上午9:30-12:00

地点：东校区财科馆317会议室

【讲座一】Title: Optimizing Inventory Control Policy with Lead Time and Lost Sales

Abstract: We study a periodic-review lost-sales inventory system with constant lead times, in which nonnegative demand is independently and identically distributed (i.i.d.), with an unknown distribution except for its mean and variance. To address the challenges posed by lost sales, we formulate a zero-sum game in which the firm selects an ordering policy to maximize long-run average profit, while Nature (the firm's adversary) selects a demand distribution to minimize the firm's steady-state profit. This framework allows us to derive Nature's dominant strategy as a two-point distribution when playing against any feasible ordering policy. Leveraging this result, we characterize the firm's optimal base-stock level, which achieves the equilibrium profit of the game. Our analysis shows that, when facing Nature's equilibrium strategy, several ordering policies, including capped base-stock, projected inventory level, and fixed non-stockout probability, generate identical ordering patterns and achieve the same optimal outcome, making them operationally equivalent. Our robust base-stock policy, which depends solely on the mean and variance of demand, offers a distribution-free solution and facilitates distribution-free implementation, making it a high-quality benchmark for both researchers and practitioners. Numerical experiments demonstrate that when the true demand distribution is unknown and only moment-based estimates are available, our robust policy outperforms alternative approaches, effectively reducing losses caused by distributional mis-specification.

【讲座二】Title: Multi-Sourcing Procurement Management: A Closed-Form Mean-Variance Approach

Abstract: In the post-pandemic era, multi-sourcing is rapidly becoming the preferred approach for companies to drive optimized cost, quality and turnaround times. However, multi-sourcing systems present a myriad of challenges in designing an effective planning model. In this paper, we propose a robust capacity planning model with multiple supply sources, and demonstrate how the capacity plan can be efficiently solved via a parsimonious mean-variance approach. We apply the max-min criterion to design a distributionally robust multi-source capacity plan. We use a new approach to deriving a set of optimality conditions on the robust capacity plan. These conditions enable us to derive the worst distribution, the optimal robust capacity vector, and the worst-case expected profit in closed form. The new approach bypasses numerous tedious intermediate procedures in the traditional distributionally robust optimization literature and allows us to derive the optimal solution based on exogenous cost parameters. This closed-form solution appears to be hitherto unknown and has important ramifications for the multi-sourcing capacity planning problem. Our findings reveal that, despite the complexity of multi-sourcing, the worst-case demand scenario can be reduced to just (n+1) distinct outcomes, structured by two key sequences derived from supplier characteristics. The optimal capacity plan has a clear structure--allocations align with the midpoints between these demand scenarios. Surprisingly, we also find that most of the robustness benefits of a full supplier portfolio can be achieved by engaging just the two best-matched sources. This provides a practical and cost-effective roadmap for robust capacity planning in multi-sourcing environments.

报告人简介：

李昭麟博士目前是悉尼大学性爱网站 副教授，他拥有宾夕法尼亚州立大学工商管理博士学位、新南威尔士大学会计学商学硕士学位以及上海交通大学材料科学与工业工程学士学位。自2009 年 1 月起，他一直在悉尼大学性爱网站 任教。在悉尼从事学术研究之前，李博士曾在安永会计师事务所和香港城市大学工作。李博士的研究兴趣广泛，涵盖鲁棒优化及运营与其他领域的交叉研究。已在Production and Operations Management上发表了七篇文章，是该旗舰期刊上发表文章最多的澳大利亚学者。他还在Management Science上发表了两篇文章。根据 Babbar 等人（2017 年、2018 年）在International Journal of Production Economics上的研究，李博士在运营管理和供应链管理领域分别位列亚洲前 25 名学者。