Efficiency and robustness of different bus network designs

John Zhen Fu Pang, Nasri Bin Othman, Keng Meng Ng and Christopher Monterola ()
Additional contact information
John Zhen Fu Pang: School of Physical and Mathematical Sciences, Nanyang Technological University, SPMS-04-01, 21 Nanyang Link, Singapore 637371, Singapore;
Nasri Bin Othman: Complex Systems Group, Computing Science, Institute of High Performance Computing, Agency for Science Technology and Research, 1 Fusionopolis way, 16-16 Connexis, Singapore 138632, Singapore
Keng Meng Ng: School of Physical and Mathematical Sciences, Nanyang Technological University, SPMS-04-01, 21 Nanyang Link, Singapore 637371, Singapore
Christopher Monterola: Complex Systems Group, Computing Science, Institute of High Performance Computing, Agency for Science Technology and Research, 1 Fusionopolis way, 16-16 Connexis, Singapore 138632, Singapore

International Journal of Modern Physics C (IJMPC), 2015, vol. 26, issue 03, 1-15

Abstract: We compare the efficiencies and robustness of four transport networks that can be possibly formed as a result of deliberate city planning. The networks are constructed based on their spatial resemblance to the cities of Manhattan (lattice), Sudan (random), Beijing (single-blob) and Greater Cairo (dual-blob). For a given type, a genetic algorithm is employed to obtain an optimized set of the bus routes. We then simulate how commuter travels using Yen's algorithms forkshortest paths on an adjacency matrix. The cost of traveling such as walking between stations is captured by varying the weighted sums of matrices. We also consider the number of transfersa posterioriby looking at the computed shortest paths. With consideration to distances via radius of gyration, redundancies of travel and number of bus transfers, our simulations indicate that random and dual-blob are more efficient than single-blob and lattice networks. Moreover, dual-blob type is least robust when node removals are targeted but is most resilient when node failures are random. The work hopes to guide and provide technical perspectives on how geospatial distribution of a city limits the optimality of transport designs.

Keywords: Bus network optimization; network designs; multi-objective optimization; 89.65.Lm; 89.70.Cf; 89.75.Kd (search for similar items in EconPapers)
Date: 2015
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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DOI: 10.1142/S0129183115500242

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