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Discrete Dynamics in Nature and Society
Volume 2014, Article ID 789754, 14 pages
Research Article

Routing Optimization of Intelligent Vehicle in Automated Warehouse

1School of Information Engineering, Tianjin University of Commerce, Tianjin 300134, China
2School of Computer Science and Software, Hebei University of Technology, Tianjin 300401, China

Received 11 April 2014; Accepted 12 May 2014; Published 16 June 2014

Academic Editor: Xiang Li

Copyright © 2014 Yan-cong Zhou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Routing optimization is a key technology in the intelligent warehouse logistics. In order to get an optimal route for warehouse intelligent vehicle, routing optimization in complex global dynamic environment is studied. A new evolutionary ant colony algorithm based on RFID and knowledge-refinement is proposed. The new algorithm gets environmental information timely through the RFID technology and updates the environment map at the same time. It adopts elite ant kept, fallback, and pheromones limitation adjustment strategy. The current optimal route in population space is optimized based on experiential knowledge. The experimental results show that the new algorithm has higher convergence speed and can jump out the U-type or V-type obstacle traps easily. It can also find the global optimal route or approximate optimal one with higher probability in the complex dynamic environment. The new algorithm is proved feasible and effective by simulation results.