Public transport network optimisation in PTV Visum using selection hyper-heuristics

Heyken Soares, Philipp; Ahmed, Leena; Mao, Yong; Mumford, Christine L.

Abstract

Despite the progress in the field of automatic public transport route optimisation in recent years, there exists a clear gap between the development of optimisation algorithms and their applications in real-world planning processes. In this study, we bridge this gap by developing an interface between the urban transit routing problem (UTRP) and the professional transport modelling software PTV Visum. The interface manages the differences in data requirements between the two worlds of research and allows the optimisation of public transport lines in Visum network models. This is demonstrated with the application of selection hyper-heuristics on two network models representing real-world urban areas. The optimisation objectives include the passengers’ average travel time and operators’ costs. Furthermore, we show how our approach can be combined with a mode choice model to optimise the use of public transport in relation to other modes. This feature is applied in a special optimisation experiment to reduce the number of private vehicles on a selected set of links in the network. The results demonstrate the successful implementation of our interface and the applied optimisation methods for a multi-modal public transport network.

Citation

Heyken Soares, P., Ahmed, L., Mao, Y., & Mumford, C. L. (2021). Public transport network optimisation in PTV Visum using selection hyper-heuristics. Public Transport, 13(1), 163-196. https://doi.org/10.1007/s12469-020-00249-7

• Journal Article Type: Article
• Acceptance Date: Aug 17, 2020
• Online Publication Date: Nov 17, 2020
• Publication Date: 2021-03
• Deposit Date: Sep 1, 2020
• Publicly Available Date: Nov 17, 2020
• Journal: Public Transport
• Print ISSN: 1866-749X
• Electronic ISSN: 1613-7159
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 13
• Issue: 1
• Pages: 163-196
• DOI: https://doi.org/10.1007/s12469-020-00249-7
• Public URL: https://nottingham-repository.worktribe.com/output/4872156
• Publisher URL: https://link.springer.com/article/10.1007/s12469-020-00249-7