基于分布式猴群算法的传感器优化布置方法研究

DISTRIBUTED MONKEY ALGORITHM FOR OPTIMAL SENSOR PLACEMENT

  • 摘要: 建立了针对具有较多自由度的大型结构传感器优化布置的分布式猴群算法。通过引入双重编码的方式, 克服了原猴群算法只能解决连续变量的缺陷;针对单个猴群全局搜索能力较弱的问题, 提出了一种将初始化产生的大量猴子个体按照指定的方式分配到多个猴群进行同步并行搜索的方法;考虑原猴群算法能够跳出局部最优的特点以及和声算法较强的局部搜索能力, 提出将每个猴群得到的初步最优解作为初始和声记忆库, 采用基本和声算法进行二次搜索的方法, 来获取传感器的最终布设方案。文末以大连国贸大厦为例, 进行了参数敏感性分析以及传感器优化布置方案的选择, 结果表明分布式猴群算法具有较强的全局寻优能力, 非常适用于具有较多自由度的大型结构传感器优化布置。

     

    Abstract: The distributed monkey algorithm is established for the optimal sensor placement of multi-degree- of-freedom large structures. Firstly, the problem that the original monkey algorithm can only solve the problem of continuous variables is overcome by introducing the dual-structure coding method. Then, a new method is proposed that assigning large number of individual monkeys generated by the initialization to multi-group of monkeys in a specified way and performing the parallel search. Considering that the original monkey algorithm is able to step out local optimum while the harmony search algorithm has better local search capability, the two-step search algorithm is adopted based on the basic harmony search algorithm by collecting the preliminary optimum gotten by each group of monkeys as the original harmony memory to obtain the final sensor placement scheme. Finally, the parametric sensitivity analysis and the selection of sensor placement schemes are performed on the Dalian International Trade Mansion. The results show that the distributed monkey algorithm has better global search capability and it is applicable to the sensor placement of multiple-degree-of-freedom large structures.

     

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