中国物理B ›› 2011, Vol. 20 ›› Issue (4): 48103-048103.doi: 10.1088/1674-1056/20/4/048103

• INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇    下一篇

Memoryless cooperative graph search based on the simulated annealing algorithm

候健, 颜钢锋, 樊臻   

  1. Department of Systems Science and Engineering, Zhejiang University, Hangzhou 310027, China
  • 收稿日期:2010-10-24 修回日期:2010-11-16 出版日期:2011-04-15 发布日期:2011-04-15

Memoryless cooperative graph search based on the simulated annealing algorithm

Hou Jian(候健), Yan Gang-Feng(颜钢锋), and Fan Zhen(樊臻)   

  1. Department of Systems Science and Engineering, Zhejiang University, Hangzhou 310027, China
  • Received:2010-10-24 Revised:2010-11-16 Online:2011-04-15 Published:2011-04-15

摘要: We have studied the problem of reaching a globally optimal segment for a graph-like environment with a single or a group of autonomous mobile agents. Firstly, two efficient simulated-annealing-like algorithms are given for a single agent to solve the problem in a partially known environment and an unknown environment, respectively. It shows that under both proposed control strategies, the agent will eventually converge to a globally optimal segment with probability 1. Secondly, we use multi-agent searching to simultaneously reduce the computation complexity and accelerate convergence based on the algorithms we have given for a single agent. By exploiting graph partition, a gossip-consensus method based scheme is presented to update the key parameter--radius of the graph, ensuring that the agents spend much less time finding a globally optimal segment.

Abstract: We have studied the problem of reaching a globally optimal segment for a graph-like environment with a single or a group of autonomous mobile agents. Firstly, two efficient simulated-annealing-like algorithms are given for a single agent to solve the problem in a partially known environment and an unknown environment, respectively. It shows that under both proposed control strategies, the agent will eventually converge to a globally optimal segment with probability 1. Secondly, we use multi-agent searching to simultaneously reduce the computation complexity and accelerate convergence based on the algorithms we have given for a single agent. By exploiting graph partition, a gossip-consensus method based scheme is presented to update the key parameter—radius of the graph, ensuring that the agents spend much less time finding a globally optimal segment.

Key words: search, simulated annealing, graph partition, globally optimal

中图分类号:  (Cold working, work hardening; annealing, post-deformation annealing, quenching, tempering recovery, and crystallization)

  • 81.40.Ef
05.65.+b (Self-organized systems) 93.85.Bc (Computational methods and data processing, data acquisition and storage)