Two-Level Planning of Customized Bus Routes Based on Uncertainty Theory
Bing Zhang,
Zhishan Zhong,
Zi Sang,
Mingyang Zhang and
Yunqiang Xue
Additional contact information
Bing Zhang: School of Transportation and Logistics, East China Jiaotong University, Nanchang 330013, China
Zhishan Zhong: School of Transportation and Logistics, East China Jiaotong University, Nanchang 330013, China
Zi Sang: School of Transportation and Logistics, East China Jiaotong University, Nanchang 330013, China
Mingyang Zhang: School of Architecture and Civil Engineering, Jiangxi V&T College Communications, Nanchang 330013, China
Yunqiang Xue: School of Transportation and Logistics, East China Jiaotong University, Nanchang 330013, China
Sustainability, 2021, vol. 13, issue 20, 1-14
Abstract:
The optimization problem of customized bus routes is affected by uncertain factors in reality; therefore, this paper introduces uncertainty theory to study the above problem. A two-level planning model that takes the maximum total revenue of the bus company as the upper-level goal and the minimum total travel cost of passengers as the lower-level goal is established, using uncertainty theory to study and solve practical problems with uncertain factors. The genetic algorithm is used to solve the model, and the feasibility of the model is verified through a case study. The research results show that the application of the two-level model of customized bus route planning based on uncertain vehicle operating time established in this paper to customize bus route planning can take into account the travel needs of passengers and high-quality experiences while also bringing benefits to enterprises and achieving a win–win situation. The research in this article provides theoretical support for the optimization of customized bus routes.
Keywords: customized bus; uncertainty theory; route optimization; genetic algorithm; two-level planning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/2071-1050/13/20/11418/pdf (application/pdf)
https://www.mdpi.com/2071-1050/13/20/11418/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:20:p:11418-:d:657576
Access Statistics for this article
Sustainability is currently edited by Ms. Alexandra Wu
More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().