无线传感器网络的改进GASA优化设计

无线传感器网络由大量传感器节点构成,因此对网络整体造价特别敏感．优化设计传感器网络构成,可以在满足监测精度的同时最小化网络造价．本文提出了一种GA和SA结合的改进GASA优化设计方法,解决由异类、多级传感器组成的无线传感器网络的优化设计问题．该方法采用特殊设计的排序组合算子提高GA的并行搜索能力．降低异类、多级传感器带来的复杂性;通过最优可行化处理加速搜索过程;利用SA的概率突跳特性避免陷入局部极小值,提高局部搜索能力．仿真实验表明,改进的GASA方法可以快速、有效地解决异类、多级传感器优化问题．

Optimal designs of wireless sensor network by adapted GASA

Wireless sensor network, consisting of lots of sensor nodes, is critical about the cost of entire network. The optimal design of wireless sensor network can minimize the cost of network and fulfill the desired accuracy of detection. An adapted GASA approach, which combines genetic algorithm (GA) and simulated annealing (SA), is developed to optimize the design of wireless sensor network consisted of multi-class, multi-level sensors. The sort-combination operator is specially designed to boost the ability of parallel search of GA and to reduce the complexity of multi-class, multi-level sensors. Optimal feasiblility is also adopted to accelerate the search procession and SA is used to enhance the ability of local search. Finally, the results obtained by GA, SA and the adapted GASA are compared, and three major characters of the adapted GASA are analyzed.