Abstract
The intelligent schedule of vehicles operation is one of the problems which need to be solved in the dispatching system of public transit vehicles, it relates to the development of the city and civic daily life. In this paper, a transit vehicle scheduling optimization algorithm which balancing between the benefits of bus companies and passengers is proposed. The glowworm swarm optimization (GSO) with random disturbance factor, namely R-GSO is applied to the schedule of vehicles. Finally, we provide some comparisons of R-GSO with artificial fish-swarm algorithm, particle swarm optimization and GSO, the simulation results show R-GSO algorithm has higher efficiency and is an effective way to optimize the public transit vehicle dispatching.
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Acknowledgments
This work is supported by National Science Foundation of China under Grant No. 61165015. Key Project of Guangxi Science Foundation under Grant No. 2012GXNSFDA053028, Key Project of Guangxi High School Science Foundation under Grant No. 20121ZD008 and the Funded by Open Research Fund Program of Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China under Grant No. IPIU01201100.
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Zhou, Y., Luo, Q. & Liu, J. Glowworm Swarm Optimization for Dispatching System of Public Transit Vehicles. Neural Process Lett 40, 25–33 (2014). https://doi.org/10.1007/s11063-013-9308-7
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DOI: https://doi.org/10.1007/s11063-013-9308-7