东北大学学报(自然科学版) ›› 2004, Vol. 25 ›› Issue (10): 934-937.DOI: -

• 论著 • 上一篇    下一篇

求解通信优化问题的一种微粒群优化方法

原萍;王光兴;张洋洋   

  1. 东北大学信息科学与工程学院;东北大学信息科学与工程学院;东北大学信息科学与工程学院 辽宁沈阳 110004
  • 收稿日期:2013-06-24 修回日期:2013-06-24 出版日期:2004-10-15 发布日期:2013-06-24
  • 通讯作者: Yuan, P.
  • 作者简介:-
  • 基金资助:
    国家高技术研究发展计划项目(2002AA784030)·

Particle swarm optimization approach of solving communication optimization problems

Yuan, Ping (1); Wang, Guang-Xing (1); Zhang, Yang-Yang (1)   

  1. (1) Sch. of Info. Sci. and Eng., Northeastern Univ., Shenyang 110004, China
  • Received:2013-06-24 Revised:2013-06-24 Online:2004-10-15 Published:2013-06-24
  • Contact: Yuan, P.
  • About author:-
  • Supported by:
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摘要: 简述了微粒群优化算法的原理、流程及其参数,在此基础上,针对其在通信中的应用,提出了一种基于分布式计算的多目标微粒群算法分割域多目标PSO算法(简称DRMPSO),并将其用于基站优化问题·仿真研究结果表明,它能很好地解决移动通信中的基站优化问题,并可被有效推广到处理诸如信道分配、网络拓扑优化设计、IP组播、Adhoc簇结构及组播路由等通信服务·

关键词: 微粒群优化算法, 多目标优化, 分布式计算, 基站规划, 遗传算法, 组播

Abstract: Briefly introduces the principle, procedure and relevant parameters of the particle swarm optimization approach. Then, a multiobjective particle swarm optimization or divided range multiobjective particle swarm optimization (DRMPSO) based on distributed computation is presented to solve the base station placement problem. The simulation results indicate the effectiveness of DRMPSO and it is convincible that DRMPSO is an efficient way to solve other problems in communications, such as channel assignment, network topological design, IP multicast, Ad hoc networks clustering, WLAN multicast.

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