基于改进布谷鸟算法的无线传感网络覆盖多目标优化

Wireless Sensor Coverage Multi-objective Optimization Improved Based on Cuckoo Search Algorithm

对布谷鸟算法改进了改进,运用改进的布谷鸟算法对无线传感器覆盖进行了优化.以覆盖率、节点利用率、网络能耗均衡系数为综合优化目标,建立了无线传感器覆盖多目标优化函数.针对普通布谷鸟算法后期搜索能力弱,容易陷入局部极限的缺陷,采取了发现概率和搜索步长自适应特征的改进措施.仿真结果显示方法有较好的优化效果.与遗传算法相比,覆盖率提高了6.73%;利用率减少了16.66%,能耗均衡系数减少17.82.

The cuckoo algorithm is improved by using the cuckoo algorithm to optimize wireless sensor coverage. We use the coverage ratio, the node utilization ratio and the network energy consumption balance coefficient as the comprehensive optimization goal, the multi objective optimization function of wireless sensor coverage is established. According to the common cuckoo algorithm＇s weak searching ability, the defect is easy to fall into local limit, the improved measures to find the adaptive features of the discovery probability and the search step size were adopted. The simulation results show that the method has better optimization effect. Compared with genetic algorithm,the coverage rate is increased by 6.73%, the utilization rate is reduced by 16.66% ,and the energy consumption balance coefficient is reduced by 17.82.