Abstract
Carpooling is a flexible shared transportation system which can effectively reduce the vehicle numbers and fuel consumption. Although many carpooling systems have been proposed, most of them lack practicality, veracity, and efficiency. In this paper, we propose a new useful variant model of the long-term carpooling problem which involves multiple origins and one destination. Such problems commonly occur in a wide number of carpooling situations in real-world scenarios. Our work is motivated by the practical needs to solve environmental pollution, parking problems, traffic jams and low utilization of resources. A Tabu search algorithm is proposed in this paper to solve the carpooling problem. The proposed algorithm aims at a wide range of passenger distribution and routing problems. The computational results based on real world user data show the effectiveness of the proposed algorithm. Moreover, we developed a mobile application based on our carpooling model.
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Acknowledgments
Defu Zhang would like to thank his supervisor Prof. Wenqi Huang who taught him a great deal about research. This work was in memory of Prof. Wenqi Huang and was partially supported by the National Nature Science Foundation of China (Grant No. 61272003) and University of Macau (Grant No. MYRG041(Y1-L1)-FST13-SYW and MYRG2015-00054-FST). At last, the authors would like to thank all reviewers for their valuable comments that help improve this paper.
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Huang, C., Zhang, D., Si, YW. et al. Tabu search for the real-world carpooling problem. J Comb Optim 32, 492–512 (2016). https://doi.org/10.1007/s10878-016-0015-y
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DOI: https://doi.org/10.1007/s10878-016-0015-y