An Optimized Artificial Bee Colony Algorithm for the Shortest Path Planning Problem

Considering the shortcomings of traditional artificial bee colony algorithm in slow convergence and easily falling into local optimum, this paper presents an optimized artificial bee colony algorithm, and use it to solve the shortest path planning problem. First, the artificial bee colony algorithm is designed to solve the shortest path planning problem. Second, the genetic hybrid genes, elite reserved strategy, and dynamic scout bees are introduced to improve the performance of traditional artificial bee colony algorithm. Finally, the proposed optimized artificial bee colony algorithm is compared with the traditional bee colony algorithm for solving the same problem in the tested area. The results show that the optimized artificial bee colony algorithm has a better performance than the traditional artificial bee colony algorithm in solving the shortest path planning problem.

• Record URL:
  https://doi.org/10.1061/9780784481523.262
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784481523
• Supplemental Notes:
  • © 2018 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Zheng, Jian
  • Zhang, Zhen
• Conference:
  • 18th COTA International Conference of Transportation Professionals
  • Location: Beijing , China
  • Date: 2018-7-5 to 2018-7-8
• Publication Date: 2018-7

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 2639-2648
• Monograph Title: CICTP 2018: Intelligence, Connectivity, and Mobility

Subject/Index Terms

• TRT Terms: Routing; Shortest path algorithms; Trajectory control
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01871638
• Record Type: Publication
• ISBN: 9780784481523
• Files: TRIS, ASCE
• Created Date: Jan 24 2023 9:33AM