A Data-Driven Timetable Optimization of Urban Bus Line Based on Multi-Objective Genetic Algorithm

Reasonable bus timetable can reduce the operating costs of bus company and improve the quality of bus services. A data-driven method is proposed to optimize bus timetable in this study. Firstly, a bi-objective optimization model is constructed considering minimize the total waiting time of passenger...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems Jg. 22; H. 4; S. 2417 - 2429
Hauptverfasser:	Tang, Jinjun, Yang, Yifan, Hao, Wei, Liu, Fang, Wang, Yinhai
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.04.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	bus timetable Companies data-driven method Dwell time Encoding Genetic algorithms Global Positioning System Global positioning systems GPS multi-objective non-dominated sorting genetic algorithm-II (NSGA-II) Optimization Passengers Scheduling Smart cards Sorting algorithms Time dependence Timetables Travel time Urban transit Urban transportation
ISSN:	1524-9050, 1558-0016
Online-Zugang:	Volltext
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