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http://dx.doi.org/10.12815/kits.2020.19.5.82

Study on Multi-vehicle Routing Problem Using Clustering Method for Demand Responsive Transit  

Kim, Jihu (Dept. of Civil & Environmental Eng., KAIST)
Kim, Jeongyun (Dept. of Civil & Environmental Eng., KAIST)
Yeo, Hwasoo (Dept. of Civil & Environmental Eng., KAIST)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.19, no.5, 2020 , pp. 82-96 More about this Journal
Abstract
The Demand Responsive Transit (DRT) system is the flexible public transport service that determines the route and schedule of the service vehicles according to users' requests. With increasing importance of public transport systems in urban areas, the development of stable and fast routing algorithms for DRT has become the goal of many researches over the past decades. In this study, a new heuristic method is proposed to generate fast and efficient routes for multiple vehicles using demand clustering and destination demand priority searching method considering the imbalance of users' origin and destination demands. The proposed algorithm is tested in various demand distribution scenarios including random, concentration and directed cases. The result shows that the proposed method reduce the drop of service ratio due to an increase in demand density and save computation time compared to other algorithms. In addition, compared to other clustering-based algorithms, the walking cost of the passengers is significantly reduced, but the detour time and in-vehicle travel time of the passenger is increased due to the detour burden.
Keywords
Clustering; Demand responsive transit; Vehicle routing problem; Heuristic method;
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