期刊
PUBLIC TRANSPORT
卷 11, 期 2, 页码 379-412出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s12469-019-00208-x
关键词
Public transport; Route optimisation; Network design; Benchmark instance; Genetic algorithm
资金
- Leverhulme Programme [RP2013-SL-015]
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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