A Green Demand-Responsive Airport Shuttle Service Problem with Time-Varying Speeds
This study proposes a multiobjective mixed integer linear programming (MOMILP) model for a demand-responsive airport shuttle service. The approach aims to assign a set of alternative fuel vehicles (AFVs) located at different depots to visit each demand point within the specified time and transport a...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2020/9853164 |
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| author | Ming Wei Binbin Jing Jian Yin Yang Zang |
| author_facet | Ming Wei Binbin Jing Jian Yin Yang Zang |
| author_sort | Ming Wei |
| collection | DOAJ |
| description | This study proposes a multiobjective mixed integer linear programming (MOMILP) model for a demand-responsive airport shuttle service. The approach aims to assign a set of alternative fuel vehicles (AFVs) located at different depots to visit each demand point within the specified time and transport all of them to the airport. The proposed model effectively captures the interactions between path selection and environmental protection. Moreover, users with flexible pick-up time windows, the time-varying speed of vehicles on the road network, and the limited fuel for the route duration are also fully considered in this model. The work aims at simultaneously minimizing the operating cost, vehicle fuel consumption, and CO2 emissions. Since this task is an NP-hard problem, a heuristic-based nondominated sorting genetic algorithm (NSGA-II) is also presented to find Pareto optimal solutions in a reasonable amount of time. Finally, a real-world example is provided to illustrate the proposed methodology. The results demonstrate that the model not only selects an optimal depot for each AFV but also determines its route and timetable plan. A sensitivity analysis is also given to assess the effect of early/late arrival penalty weights and the number of AFVs on the model performance, and the difference in quality between the proposed and traditional models is compared. |
| format | Article |
| id | doaj-art-fd1bf85eb637410caeac82659a36a16b |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-fd1bf85eb637410caeac82659a36a16b2025-02-03T06:46:08ZengWileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/98531649853164A Green Demand-Responsive Airport Shuttle Service Problem with Time-Varying SpeedsMing Wei0Binbin Jing1Jian Yin2Yang Zang3School of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, ChinaSchool of Transportation, Nantong University, Nantong 226019, ChinaSchool of Transportation, Nantong University, Nantong 226019, ChinaSchool of Transportation, Nantong University, Nantong 226019, ChinaThis study proposes a multiobjective mixed integer linear programming (MOMILP) model for a demand-responsive airport shuttle service. The approach aims to assign a set of alternative fuel vehicles (AFVs) located at different depots to visit each demand point within the specified time and transport all of them to the airport. The proposed model effectively captures the interactions between path selection and environmental protection. Moreover, users with flexible pick-up time windows, the time-varying speed of vehicles on the road network, and the limited fuel for the route duration are also fully considered in this model. The work aims at simultaneously minimizing the operating cost, vehicle fuel consumption, and CO2 emissions. Since this task is an NP-hard problem, a heuristic-based nondominated sorting genetic algorithm (NSGA-II) is also presented to find Pareto optimal solutions in a reasonable amount of time. Finally, a real-world example is provided to illustrate the proposed methodology. The results demonstrate that the model not only selects an optimal depot for each AFV but also determines its route and timetable plan. A sensitivity analysis is also given to assess the effect of early/late arrival penalty weights and the number of AFVs on the model performance, and the difference in quality between the proposed and traditional models is compared.http://dx.doi.org/10.1155/2020/9853164 |
| spellingShingle | Ming Wei Binbin Jing Jian Yin Yang Zang A Green Demand-Responsive Airport Shuttle Service Problem with Time-Varying Speeds Journal of Advanced Transportation |
| title | A Green Demand-Responsive Airport Shuttle Service Problem with Time-Varying Speeds |
| title_full | A Green Demand-Responsive Airport Shuttle Service Problem with Time-Varying Speeds |
| title_fullStr | A Green Demand-Responsive Airport Shuttle Service Problem with Time-Varying Speeds |
| title_full_unstemmed | A Green Demand-Responsive Airport Shuttle Service Problem with Time-Varying Speeds |
| title_short | A Green Demand-Responsive Airport Shuttle Service Problem with Time-Varying Speeds |
| title_sort | green demand responsive airport shuttle service problem with time varying speeds |
| url | http://dx.doi.org/10.1155/2020/9853164 |
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