论坛主题：Toward Reliable Design of Service Facility Location: Addressing the Threat of Probabilistic Disruptions

  主讲嘉宾：Yanfeng Ouyang

  时间：2015年8月9日（周日）上午10:00

  地点：交通运输工程学院436会议室

  主讲人简介：

  Yanfeng Ouyang is tenured Associate Professor, P.F. Kent Endowed Faculty Scholar of Civil and Environmental Engineering, and D.B. Willett Faculty Scholar at the University of Illinois at Urbana-Champaign (UIUC). He received his Ph.D. in civil engineering from the University of California at Berkeley in 2005. He currently serves as a Department Editor of IIE Transactions, an Area Editor of Networks and Spatial Economics, an Associate Editor of Transportation Science, an Associate Editor of Transportmetrica B, and a Guest (Co-)Editor of Transportation Research Part B, Journal of Intelligent Transportation Systems, and the International Journal of Rail Transportation. He is also on the editorial advisory board of Transportation Research Part B and the Journal of Infrastructure Systems.  He received a Walter L. Huber Research Prize from the American Society of Civil Engineers in 2015, a Faculty Early Career Development (CAREER) Award from the U.S. National Science Foundation in 2008, a High Impact Project Award from the Illinois Department of Transportation in 2014, an Engineering Council Outstanding Advisor Award from UIUC in 2014, a Xerox Award for Faculty Research from UIUC in 2010, and a Gordon F. Newell Award from Berkeley in 2005, among others.

  内容简介：

  While planning service networks to serve spatially distributed customers, we consider the case where facilities are subject to probabilistic failure (due to reasons such as adverse weather or disasters). If a facility fails, its customers either lose service and incur a high penalty, or have to seek farther facilities and bear excessive service costs. We mainly focus on planning optimal facility locations as well as customer assignment strategies for a supply chain, so as to minimize the expected system costs under normal and failure scenarios. We start with the basic case where site-specific and independent facility disruptions occur in the traditional facility location problem context. Then we show extensions where inbound and outbound deliveries are conducted via vehicle routing, and where facility disruptions exhibit positive and/or negative spatial correlations (e.g. when interdependent facilities are exposed to similar hazards or the risks of cascading failures). We will briefly show how to develop compact mixed-integer program models that can be solved by customized algorithms such as Lagrangian relaxation. We will also present a series of continuum approximation models that not only serve as very efficient heuristic method to find near-optimum solutions for large-scale systems, but also help provide useful managerial insights (e.g., solution robustness to input data errors, and effects of system heterogeneity).

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