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Modelling and simulation of hierarchical scheduling of real‐time responsive customised bus
Author(s) -
Han Shuang,
Fu Hui,
Zhao Jiahong,
Lin Junzhou,
Zeng Weiliang
Publication year - 2020
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2020.0138
Subject(s) - scheduling (production processes) , computer science , service (business) , schedule , operations research , sorting , genetic algorithm , real time computing , transport engineering , engineering , operations management , economy , machine learning , economics , programming language , operating system
A real‐time responsive customised bus (RTRCB) provides demand‐oriented and shared‐ride service for passengers with random travel demands. Unlike other works in the literature, the authors developed a hierarchical methodology to optimise the RTRCB schedule. It involves a trade‐off between the interests of the transporter and those of the passengers. After minimising the initial travel distance while maintaining a wide service range, the bus routes are planned holistically based on the main travel locations. Based on the initial routes, the buses are dispatched to satisfy the real‐time travel demands. The procedure for solving the proposed problem is developed by modifying the genetic algorithm (GA) and non‐dominated sorting GA with elite strategy. The proposed method is applied to a real‐life problem in the city of Shenzhen, and certain extensional analyses are performed to demonstrate their feasibility. The computational results show that: (i) the travel distance limitation and tortuosity ratio of the bus route play the most important roles in planning bus routes; (ii) the designation of all the initial bus stops as the control stops results in comparatively stable service for more passengers; and (iii) a better service performance can be achieved by introducing the soft time window strategy with an acceptable delivery delay.

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