Assessing the role of network topology in transportation network resilience

The abstract representation of a transportation system as a network of nodes and interconnecting links, whether that system involves roadways, railways, sea links, airspace, or intermodal combinations, defines a network topology. Among the most common in the context of transportation systems are the grid, ring, hub-and-spoke, complete, scale-free and small-world networks. This paper investigates the role of network topology, and the topology’s characteristics, in a transportation system’s ability to cope with disaster. Specifically, the paper hypothesizes that the topological attributes of a transportation system significantly affect its resilience to disaster events. Resilience accounts for not only the innate ability of the system to absorb externally induced changes, but also cost-effective and efficient, adaptive actions that can be taken to preserve or restore performance post-event. Comprehensive and systematically designed numerical experiments were conducted on 17 network structures with some relation to transportation system layout. Resilience of these network structures in terms of throughput, connectivity or compactness was quantified. Resilience is considered with and without the benefits of preparedness and recovery actions. The impact of component-level damage on system resilience is also investigated. A comprehensive, systematic analysis of results from these experiments provides a basis for the characterization of highly resilient network topologies and conversely identification of network attributes that might lead to poorly performing systems.

[1]  Elise Miller-Hooks,et al.  Measuring the performance of transportation infrastructure systems in disasters: a comprehensive review , 2015 .

[2]  Erik Jenelius,et al.  Road network vulnerability analysis of area-covering disruptions: A grid-based approach with case study , 2012 .

[3]  Ziyou Gao,et al.  URBAN TRANSIT SYSTEM AS A SCALE-FREE NETWORK , 2004 .

[4]  Gilbert Laporte,et al.  The integer L-shaped method for stochastic integer programs with complete recourse , 1993, Oper. Res. Lett..

[5]  Sybil Derrible,et al.  The complexity and robustness of metro networks , 2010 .

[6]  Alan T. Murray,et al.  Comparative Approaches for Assessing Network Vulnerability , 2008 .

[7]  Juan Carlos García-Palomares,et al.  Measuring the vulnerability of public transport networks , 2014 .

[8]  Guy Theraulaz,et al.  The Topological Fortress of Termites , 2008, BIOWIRE.

[9]  Gao Zi-You,et al.  Topological Effects on the Performance of Transportation Networks , 2007 .

[10]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[11]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[12]  Morton E. O’Kelly,et al.  Network Hub Structure and Resilience , 2014, Networks and Spatial Economics.

[13]  I. Kelman,et al.  Geographies of resilience , 2015 .

[14]  W. Adger Social and ecological resilience: are they related? , 2000 .

[15]  Yan Li Assessing Survivability of the Beijing Subway System , 2014 .

[16]  Michael T. Gastner,et al.  The spatial structure of networks , 2006 .

[17]  A. Rose DEFINING AND MEASURING ECONOMIC RESILIENCE TO DISASTERS , 2004 .

[18]  Elise Miller-Hooks,et al.  Measuring and maximizing resilience of freight transportation networks , 2012, Comput. Oper. Res..

[19]  C. S. Holling Resilience and Stability of Ecological Systems , 1973 .

[20]  Peter Nijkamp,et al.  Transport resilience and vulnerability: The role of connectivity , 2015 .

[21]  Aura Reggiani,et al.  Accessibility and Impedance Forms: Empirical Applications to the German Commuting Network , 2011 .

[22]  J. Y. Yen Finding the K Shortest Loopless Paths in a Network , 1971 .

[23]  Elise Miller-Hooks,et al.  Resilience: An Indicator of Recovery Capability in Intermodal Freight Transport , 2012, Transp. Sci..

[24]  Massimo Marchiori,et al.  Is the Boston subway a small-world network? , 2002 .