Weighted Complex Network Analysis of Pakistan Highways

The structure and properties of public transportation networks have great implications in urban planning, public policies, and infectious disease control. This study contributes a weighted complex network analysis of travel routes on the national highway network of Pakistan. The network is responsible for handling 75 percent of the road traffic yet is largely inadequate, poor, and unreliable. The highway network displays small world properties and is assortative in nature. Based on the betweenness centrality of the nodes, the most important cities are identified as this could help in identifying the potential congestion points in the network. Keeping in view the strategic location of Pakistan, such a study is of practical importance and could provide opportunities for policy makers to improve the performance of the highway network.

[1]  Neelima Gupte,et al.  Gradient mechanism in a communication network. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  X. Cai,et al.  Empirical analysis of a scale-free railway network in China , 2007 .

[3]  Neelima Gupte,et al.  Congestion and decongestion in a communication network. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Pan Di,et al.  Weighted complex network analysis of travel routes on the Singapore public transportation system , 2010 .

[5]  M. H. Everdell.  Statistical mechanics and its chemical applications , 1975 .

[6]  Ganesh Bagler,et al.  Analysis of the airport network of India as a complex weighted network , 2004, cond-mat/0409773.

[7]  Arnab Chatterjee,et al.  Small-world properties of the Indian railway network. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

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

[9]  Ulrik Brandes,et al.  On variants of shortest-path betweenness centrality and their generic computation , 2008, Soc. Networks.

[10]  J. Hyman,et al.  Scaling laws for the movement of people between locations in a large city. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[11]  R. Guimerà,et al.  The worldwide air transportation network: Anomalous centrality, community structure, and cities' global roles , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[12]  SATYAM MUKHERJEE,et al.  Statistical analysis of the road network of India , 2012, 1203.0313.

[13]  W. Li,et al.  Statistical analysis of airport network of China. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  M E J Newman.  Assortative mixing in networks. , 2002, Physical review letters.

[15]  J. Hołyst,et al.  Statistical analysis of 22 public transport networks in Poland. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  Feng Liu,et al.  Empirical analysis of the ship-transport network of China. , 2007, Chaos.

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