Mathematical models for carpooling considering driver absence: Comparative analysis and heuristic strategies

Carpooling reduces travel costs, alleviates traffic congestion, and increases social interaction, making it an economical, environmentally friendly, and efficient mode of transportation. Considering the uncertainties involved in carpooling, this paper presents mathematical models to find alternative...

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Vydáno v:Computers & industrial engineering Ročník 210; s. 111577
Hlavní autoři: Wang, Wushuang, Li, Yu, Tan, Yiliu, Kobayashi, Ryotaro, Hashikami, Hidenobu, Shigeno, Maiko
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.12.2025
Témata:
Absence
Carpooling
Heuristic algorithm
Integer programming model
Operation route
Temporary route
Temporary route
Operation route
Absence
Integer programming model
Heuristic algorithm
Carpooling
ISSN:0360-8352
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Shrnutí:Carpooling reduces travel costs, alleviates traffic congestion, and increases social interaction, making it an economical, environmentally friendly, and efficient mode of transportation. Considering the uncertainties involved in carpooling, this paper presents mathematical models to find alternative routes for a commuter carpooling service in the event of last-minute driver absences. When a driver cancels their carpooling service, it becomes necessary to secure alternative commuting routes for the riders scheduled to ride in that driver’s car. The proposed models construct alternative routes that minimize deviations from the initially planned route, ensuring that another driver can efficiently pick up and drop off the riders. Considering computational efficiency, a population-based heuristic algorithm is designed for large-scale problems. Numerical experiments based on real data are conducted to compare three different models. The superiority of our algorithm is also confirmed through these experiments. A commuting route is constructed in advance that accounts for potential driver absence, and this alternative route effectively prevents significant changes in the number of commuters riding together and the departure times, even in the event of driver absence. •Proposed models to minimize route deviations in carpooling due to driver absences.•Incorporated route difference impacts on both drivers and riders in models.•Developed a heuristic algorithm to solve large-scale problems effectively.•Evaluated carpooling models using real-world data across seven key performance metrics.
ISSN:0360-8352
DOI:10.1016/j.cie.2025.111577