Topological Resilience Analysis of Supply Networks under Random Disruptions and Targeted Attacks Wenjun Wang, W. Nick Street, and Renato E. deMatta Department of Management Sciences University of Iowa Iowa City, IA 52242, USA {wenjun-wang, nick-street, renato-dematta}@uiowa.edu Abstract—Along with the rapid advancement of information technology, the traditional hierarchical supply chain has been quickly evolving into a variety of supply networks, which usually incorporate a large number of entities into complex graph topologies. The study of the resilience of supply networks is an important challenge. In this paper, we exploit the resilience embedded in the network topology by investigating in depth the multiple-path reachability of each demand node to other nodes, and propose a novel network resilience metric. We also develop new supply-network growth mechanisms that reflect the heterogeneous roles of different types of nodes in the supply network. We incorporate them into two fundamental network topologies (i.e. random-graph network and scale-free network), and evaluate their resilience against both random disruptions and targeted attacks using the new resilience metric. The exper- imental results verify the validity of our resilience metric and the effectiveness of our growth model. This research provides a generic framework and important insights into the construction and resilience analysis of complex supply networks. I. I NTRODUCTION The supply chain is the construction and management of the flow of goods among suppliers, distributors, retailers, and customers. Traditional supply chains usually maintain a hierarchical structure with a linear flow of goods from suppliers to customers via distributors and retailers. Due to the globalization and fast development of technology, the basic supply chain system has become much more sophisticated, and it has rapidly evolved into dynamic complex networks in which links can occur not only between units of different types, but also between units of the same type. For example, some large retailers may distribute goods to small retailers. While the supply network plays such an important role in product distribution systems, its sustainability (or say, surviv- ability) becomes an important concern. It has also become an interesting research topic that has drawn considerable attention and extensive studies. Some of the challenging questions regarding the resilience of complex supply networks are as fol- lows. What are the principles that govern how supply networks arise and develop? How resilient is a supply network against random and/or targeted disruptions? How do we measure resilience, and how is it related to the network topology? How can we build resiliency in a supply-network design? There are many such interesting but challenging questions regarding the resilience analysis of complex supply networks. Previous research [1][2] have revealed that supply networks share many characteristics that most real-world networks commonly have, and the graph topology of the supply network has great impact on its resilience against disruptions. In this paper, we first propose a new resilience metric that captures the reachability-based robustness encoded in the network topology in a more accurate and comprehensive manner. Then we present new supply-network growth models that incorporate the heterogeneous roles of units of different types into two fundamental network topologies with various attachment strategies. Using a military logistic network as a case study, we analyze the resilience of different growth mod- els by simulating the supply network under random disruptions and targeted attacks. Experimental results verify the validity of our resilience metric, and demonstrate the effectiveness of our growth model. Our approach sheds light on the construction of more realistic and robust supply networks. II. RELATED WORK Supply networks are often subject to various disruptions, such as unexpected accidents, natural disasters, terrorist at- tacks, etc. When the disruption occurs, a few units or con- nections fail to operate at the onset, but the adverse impact on organizational performance may propagate in the network and eventually lead to devastating malfunction of a great component or even the entire supply system. The resilience analysis of supply-networks under random disruptions and targeted attacks has received considerable managerial attention and a lot of research work. While conventional disruption studies focus on risk miti- gation and contingency planning strategies [3][4], some re- searchers investigate the resilience of supply networks from a topological perspective. Criado et al. [5] define a quantitative measure of network vulnerability related to the graph topology. Using a multiagent-based simulation framework, Thadaka- malla et al. [6] examine how different network topologies affect the supply-network resilience against random disrup- tions and targeted attacks in terms of clustering coefficient, size of the largest connected component (LCC), characteristic path length in LCC, and maximum distance in LCC. Nair and Vidal [7] adopt the multiagent model and investigate topology-associated supply-network robustness from the per- spective of performance impacts in terms of inventory levels, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 250 ASONAM '15, August 25-28, 2015, Paris, France © 2015 ACM. ISBN 978-1-4503-3854-7/15/08 $15.00 DOI: http://dx.doi.org/10.1145/2808797.2809325