4.5 Article

Glowworm Swarm Optimization for Dispatching System of Public Transit Vehicles

Journal

NEURAL PROCESSING LETTERS
Volume 40, Issue 1, Pages 25-33

Publisher

SPRINGER
DOI: 10.1007/s11063-013-9308-7

Keywords

Public transit vehicle dispatching; Glowworm swarm optimization (GSO); Random disturbance factor; R-GSO

Funding

  1. National Science Foundation of China [61165015]
  2. Key Project of Guangxi Science Foundation [2012GXNSFDA053028]
  3. Key Project of Guangxi High School Science Foundation [20121ZD008]
  4. Open Research Fund Program of Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China [IPIU01201100]

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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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