The Multi-Type Demands Oriented Framework for Flex-Route Transit Design

Jiayi Li, Zhaocheng He () and Jiaming Zhong
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Jiayi Li: School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 518000, China
Zhaocheng He: School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 518000, China
Jiaming Zhong: School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 518000, China

Sustainability, 2022, vol. 14, issue 15, 1-23

Abstract: Flex-route transit is regarded as the feasible solution to provide flexible service for various demands. To improve the service of flex-route transit, this paper proposes a design framework with the input of multi-type demands. Firstly, according to the multi-feature-based classification method, static stations and dynamic stations are divided by hierarchical clustering algorithm based on historical demands. Secondly, in the two-stage planning method, an offline plan is generated by multi-route design model and route-design-oriented genetic algorithm based on the classified stations and the flexible combination of reserved demands and regular travel patterns. Then, an online plan is adjusted by route modification model and greedy algorithm based on the offline plan and real-time demands. Numerical experiments demonstrate the applicability of flex-route transit in the realistic road network and show that flex-route transit can transport demands more effectively and save nearly 40% of cost compared with traditional transit.

Keywords: flex-route transit; multi-type demands; station classification; two-stage planning; route-design-oriented genetic algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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