An adaptive scaled network for public transport route optimisation

Philipp Heyken Soares · Christine L. Mumford · Kwabena Amponsah · Yong Jian Mao

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Transportation Planning and Optimization Vehicle Routing Optimization Methods Transportation and Mobility Innovations

Abstract

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.

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References

1986Bus network design 1975An Algorithm for the Discrete Network Design Problem 1998Urban Bus Transit Route Network Design Using Genetic Algorithm 1991An AI‐based approach for transit route system planning and design 2010Transit network design: A procedure and an application to a large urban area 2002Genetic algorithms in bus network optimization 2015Efficient transit network design and frequencies setting multi-objective optimization by alternating objective genetic algorithm 2011Transit-network design methodology for actual-size road networks

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