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An adaptive scaled network for public transport route optimisation

Heyken Soares, Philipp; Mumford, Christine L.; Amponsah, Kwabena; Mao, Yong


Philipp Heyken Soares

Christine L. Mumford

Kwabena Amponsah

Associate Professor


We introduce an adaptive network for public transport route optimisation by scaling down the available street network to a level where optimisation methods such as genetic algorithms can be applied. Our scaling is adapted to preserve the characteristics of the street network. The methodology is applied to the urban area of Nottingham, UK, to generate a new benchmark dataset for bus route optimisation studies. All travel time and demand data as well as information of permitted start and end points of routes, are derived from openly available data. The scaled network is tested with the application of a genetic algorithm adapted for restricted route start and end points. The results are compared with the real-world bus routes.


Heyken Soares, P., Mumford, C. L., Amponsah, K., & Mao, Y. (2019). An adaptive scaled network for public transport route optimisation. Public Transport, 11(2), 379-412.

Journal Article Type Article
Acceptance Date Jun 1, 2019
Online Publication Date Jul 29, 2019
Publication Date Aug 1, 2019
Deposit Date Jun 20, 2019
Publicly Available Date Jun 20, 2019
Journal Public Transport
Print ISSN 1866-749X
Electronic ISSN 1613-7159
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 11
Issue 2
Pages 379-412
Keywords Mechanical Engineering; Management Science and Operations Research; Information Systems; Transportation
Public URL
Publisher URL


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