A Single Period Analysis of a Two-Echelon Inventory System with Dependent Supply Uncertainty

Date: 25 Oct 2011 - 25 Oct 2011

Venue: SIMTech Training Room 2, Tower Block, Level 3

This technical talk is cancelled. For enquiry on the revised schedule, please contact: Dr Yuan Xue Ming, Email:

The objective of the lecture is to present some of Professor Xu's recent research achievements in the areas of operations research and supply chain management, in particular, Inventory Management and Optimisation. She is one of the leading experts in SCM, Operations Research and Management Science.

2.30pm    Registration
3.00pm    Lecture by Prof. Susan Xu
4.00pm    Networking & Refreshment
4.30pm    End  

Disruptions and random supplies are the important sources of uncertainty that should be considered in the design and control of supply chains. There have been many real world examples in which a single catastrophic event has simultaneously degraded the capabilities of several suppliers leading to considerable erosion of profits and goodwill for a company. However, the literature on analytical models that account for the dependence nature of disruptions and its impact on supply chain performance is sparse. In this technology lecture, Prof Xu will discuss an m-manufacturer, 1-retailer, newsvendor inventory system with stochastically dependent manufacturing capacities, caused by random disruptions that may simultaneously inflict damages to the capacities of the manufacturers. She has developed the structural/analytical properties of key performance measures and optimal inventory policies for the multi-source and assembly inventory systems. She will show that stochastic dependence in disruptions can have opposite effects on system performance in the multi-source and assembly systems. While risk diversification is preferred in the multi-source system, risk concentration is preferred in the assembly system. Her results also suggest that, if the retailer ignores the effect of dependent disruptions, then in the multi-source structure, it would underestimate the cost, overestimate the fill rate, and order more units than the optimum; however, in the assembly structure, the opposite would happen. She will perform a comprehensive numerical study to validate our analytical results and generate useful managerial and operational insights for effective risk management of supply chains in the presence of dependent supply uncertainty.

About the Speaker
Dr Xu is a Professor of Management Science and Supply Chain Management at Pennsylvania State University. She is the Director of PhD Program in Smeal College of Business.  She served as the Chair of the Intercollege Dual-Title Degree Graduate Program in Operations Research at Penn State from 1998-2007.  She held visiting positions in several universities including George Mason University, University of California at Berkeley, Chinese University of Hong Kong, The Hong Kong University of Science & Technology, Georgetown University, University of Maryland, National Universityof Singapore, and Singapore Institute of Manufacturing Technology, among others. Prof. Xu’s primary research interests are centered on design, performance evaluation, simulation and optimisation of stochastic operating systems and their applications in supply chain management and service systems, telecommunication, information technology, and reliability.  In particular, she is interested in production and inventory systems, risk management of supply chain, revenue management, queueing control, stochastic ordering of multivariate stochastic processes, maintenance policies and risk analysis in reliability systems.  Her research is currently supported by NSF grants CMMI-0825960 and CMMI-1000183 and the Competitive Research Program in Smeal College of Business. She is currently an Associate Editor for Operations Research, Associate Editor for IEEE Trans on Reliability, and Editorial Board Member for Probability in Engineering and Informational Sciences.   

Pre-registration for this non-chargeable event is required for logistics and catering purposes. To reserve a place, please register online.   

Who Should Attend
Senior management staff, R&D engineer, managers, scientists, analysts from industries, academic staff and post-graduate research students.

Contact Us
For technical enquiries, please contact Dr Yuan Xue Ming, Email:
For general enquiries, please contact Alice Koh, Email: