Journal of South China University of Technology (Natural Science Edition) ›› 2008, Vol. 36 ›› Issue (8): 1-5.

• Electronics, Communication & Automation Technology •     Next Articles

New Elevator Dispatching Strategy Based on Hybrid Immune Particle Swarm Optimization Algorithm

Luo Fei  Lin Xiao-lan  Xu Yu-ge  Li Hui-juan     

  1. School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, Guangdong, China
  • Received:2007-06-18 Revised:2008-02-25 Online:2008-08-25 Published:2008-08-25
  • Contact: 罗飞（1957-），男，教授，博士生导师，主要从事人工智能及运动控制系统方面的研究． E-mail:aufeiluo@seut．edu．cn
  • About author:罗飞（1957-），男，教授，博士生导师，主要从事人工智能及运动控制系统方面的研究．
  • Supported by:

    国家自然科学基金资助项目（60774032）;广东省自然科学基金资助项目（06025724）;高等学校博士点专项科研基金新教师基金课题（20070561006）;广州市科技攻关重点项目（200722-190121）

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Abstract:

According to the complementarity of the artificial immune （AI） optimization algorithm and the particle swarm optimization （PSO） algorithm, a hybrid immune particle swarm optimization algorithm is proposed and employed to optimize the elevator dispatching in the hybrid elevator-group control system. The simulated results are then compared with those obtained by AI optimization and PSO algorithms, finding that, by using the proposed algorithm, the long waiting percentage and the run count are greatly improved, while the average waiting time is not obviously shortened. It is thus concluded that the proposed algorithm is effective in optimizing the elevator dispatching in the hybrid elevator-group control system.

Key words: artificial immune optimization algorithm, immune particle swarm, hybrid elevator-group control system, clonal selection, cellular automaton