報告題目：三維細觀力學模型與應用

報告人：張錦華 研究員

報告時間：05月12日 14:30-15:30

報告地點：民航樓1213會議室

報告内容摘要：

報告題目：航空裝備事故調查注意事項

報告人：張東方

報告時間：2023年5月15日 14:00-15:00

報告地點：将軍路校區民航樓1213會議室

報告内容摘要：

報告題目：A Co-Opetitive Game Analysis of Platform Compatibility Strategies Under Add-on Services

報告所屬學科：管理科學與工程

報告人：李武（加拿大溫莎大學）

報告時間：2023年5月12日 15:00-18:00

報告地點：經管院702會議室

報告摘要：

Large-scale platforms (LSPs) with valuation and awareness advantages have enabled competing small-scale platforms (SSPs) to be embedded in their platforms. This compatibility strategy creates a new channel, the compatible channel, through which customers can purchase services from an SSP via the LSP. Meanwhile, more platforms have been introducing add-on services to enhance their profitability. This study develops stylized game models to characterize the interaction between an LSP and an SSP, and explores their strategic and operational decisions on platform compatibility under add-on services. Our major research findings are as follows. First, we identify the conditions for platform compatibility: compatibility becomes an equilibrium strategy if the proportion of demand through the compatible channel falls within an intermediate range. Second, compatibility has opposite impacts on service pricing: At a low proportion of demand through the compatible channel, the two platforms engage in a price war; otherwise, they both raise prices. Finally, some model extensions further verify the robustness of the conclusions.

報告人簡介：

李武(Kevin W. Li)，現任加拿大溫莎大學Odette商學院教授。1991年獲廈門大學控制科學理學學士學位，1994年獲廈門大學系統工程工學碩士學位，2003年獲加拿大滑鐵盧大學系統設計工程博士學位。2011年6月~12月和2015年5月~7月由日本學術振興會(JSPS)外籍聘用研究員項目資助到東京工業大學價值與決策科學系進行訪問研究。主要研究方向：物流與供應鍊管理、決策理論與方法、沖突分析。其研究獲得三項加拿大自然科學與工程研究基金會(NSERC)發現基金項目的支持。自2001年以來，在《European Journal of Operational Research》、《IEEE Transactions on Fuzzy Systems》、《IEEE Transactions on Systems, Man, and Cybernetics》、《Information Sciences》、《International Journal of Production Economics》、《International Journal of Production Research》、《Transportation Research》、《Water Resources Research》等國際期刊發表67篇學術論文，被國内外同行廣泛引用，SCI/SSCI累計引用2552次，h指數30。現任SSCI期刊《Group Decision and Negotiation》的副主編以及其他多家SCI/SSCI期刊編委。

報告題目：體系韌性評估方法探讨

報告所屬學科：管理科學與工程

報告人：兌紅炎（鄭州大學管理學院）

報告時間：2023年5月13日 15:00-18:00

報告地點：經管學院703室

報告摘要：

鑒于體系的複雜性和動态性，提出韌性應以理解和塑造适應不斷變化的各個分層關聯子系統為出發點，構建“可感知、可預防、可恢複、可重構”體系評估方法。“可感知”，是對體系中各類主體的變化情況和變化趨勢進行感知；“可預防”，是利用機器學習及人工智能等智能化輔助工具，可自主預防各種威脅發生的概率；“可恢複”，是通過常态化、動态化、精準化的數據捕獲及時發現問題，表明故障時性能可恢複的程度或快慢；“可重構”，是基于體系關聯多層結構進行的自動調整和自我完善，應對故障的結構重組能力，實現全生命周期的閉環管理。結合智能集群對抗體系和裝備保障體系，考慮預防、降級、恢複和重構四個階段，闡述體系各層之間的協同作戰能力，提出跨域整組的韌性策略。

報告人簡介：

兌紅炎，男，鄭州大學 管理學院，教授，博士，博士生導師，河南省高校科技創新人才、河南省青年骨幹教師、學術技術帶頭人。從事複雜網絡優化（韌性、脆弱性、穩定性等）、智能集群及制造系統大數據可靠性管理（集群對抗、保障體系、機械制造系統故障診斷等）；長期從事的重要度理論成果獲得省部級自然科學獎；所提出的綜合重要度計算方法已經被美國SAS系統JMP軟件采用。主持2項國家自然科學基金、教育部規劃基金、國際合作基金、裝備發展部預研基金、科技處重大專項子課題等。發表SCI等學術期刊論文92篇，出版學術專著2部。擔任國際期刊《Journal of Risk and Reliability》，《International Journal of Mathematical, Engineering and Management Sciences》等編委。

報告題目：Taming the Long Tail: The Gambler's Fallacy in Intermittent Demand Management

報告所屬學科：管理科學與工程

報告人：畢晟（上海财經大學）

報告時間：2023年5月17日 15:00-17:00

報告地點：經管學院702室

報告摘要：

“Long tail” products with intermittent demand often tie up valuable warehouse space and capital investment for many companies. Furthermore, the paucity of demand data poses additional challenges for model estimation and performance evaluation. Traditional inventory solutions are not designed for products with intermittent demand. In this paper, we propose a new framework to optimize the choice of “replenishment timing” and “replenishment quantity” for managing the inventory metrics of long tail products, when evaluated over a finite horizon. Our analysis is motivated by a recent interesting observation that the gambler’s fallacy phenomenon actually holds in a finite number of coin tosses. We use this phenomenon to analyze the inventory problem for intermittent demand to demonstrate that classical inventory models using KPIs such as fill rate, average cost per cycle, or average cost per unit, etc., must necessarily “bias” the underlying demand distribution to account for the finite horizon effect. We provide the exact closed-form expressions of the biased distribution to account for this effect in performance evaluation. The results show that the choice of replenishment timing and replenishment quantity is essential to superior performanceon several key inventory metrics. For long tail products, the belief that it is less likely for another demand to arrive shortly after a preceding one (the gambler’s fallacy), turns out to be true when performance is tabulated over a finite horizon, even if demands across time are independent. So it pays to delay the replenishment of depleted stocks to save on holding cost and warehouse space. Managers can optimize the replenishment timing, besides choosing the replenishment quantity, to optimize the performance metrics of several classes of inventory problems. This is especially useful for companies managing a large number of long tail products.

報告人簡介：

Bi Sheng is currently an assistant professor at School of Information Management and Engineering, Shanghai University of Finance and Economics. She received her Ph.D. degree in Analytics and Operations from National University of Singapore in 2021 and her Bachelor's degree in Industrial Engineering from Nanjing University in 2016. Her research interests are in the area of data-driven optimization, supply chain management and socially responsible operations.

報告題目：Stochastic Robust Facility Location: A Nested Decomposition Approach

報告所屬學科：管理科學與工程

報告人：王曙明（中國科學院大學）

報告時間：2023年5月18日 16:00-18:00

報告地點：經管學院702室

報告摘要：

In this work, we investigate a broad class of facility location problems in the context of adaptive robust stochastic optimization. A state-wise ambiguity set is employed to model the distributional uncertainty associated with the demand in different states, where the conditional distributional characteristics in each state are described by support, mean as well as dispersion measures, which are conic representable. A robust sensitivity analysis is performed in which on the one hand we analyze the impact of the change in ambiguity set parameters (e.g., state probabilities, mean value abounds and dispersion bounds in different states) onto the optimal worst-case expected total cost using the ambiguity dual variables. On the other hand, we analyze the impact of the change in location design onto the worst-case expected second-stage cost, and show that the sensitivity bounds are fully described as the worst-case expected shadow capacity cost. As for the solution approach, we propose a nested Benders decomposition algorithm for solving the model exactly, which leverages the subgradients of the worst-case expected second-stage cost at the location decisions formed insightfully by the associated worst-case distributions. The nested Benders decomposition approach ensures a finite-step convergence, which can also be regarded as an extension of the classic L-shaped algorithm for two-stage stochastic programming to our state-wise robust stochastic facility location problem with conic representable ambiguity. Finally, the results of a series of numerical experiments are presented which justify the value of the state-wise distributional information incorporated in our robust stochastic facility location model, the robustness of the model and the performance of the exact solution approach.

報告人簡介：

中國科學院大學經濟與管理學院王曙明教授，主要從事魯棒優化與随機規劃研究及其在選址與物流網絡優化、供應鍊風險管理、庫存與收益管理、健康醫療管理等領域的應用。研究成果分别發表于Production and Operations Management, INFORMS Journal on Computing, Transportation Science, IISE Transactions, Naval Research Logistics, IEEE Trans. Cybernetics等權威雜志上。目前擔任運籌學著名期刊《Computers and Operations Research》的領域編輯(Area Editor).