改进果蝇算法在传感网部署中的应用

Novel Dichotomy Fruit Fly Optimization Algorithm in Sensor Deployment

设计了一种新的二分果蝇优化算法对传感节点的部署进行优化,每个果蝇个体代表节点部署位置。每次更新迭代时,将果蝇个体虚拟分化为二,并沿设置的不同步长更新模式开启嗅觉搜索,对比获取适应值高的个体位置作为果蝇个体视觉搜索的最优位置,然后作为节点部署位置。仿真结果表明,本文算法在覆盖率的提升方面优于基本果蝇算法、递减果蝇算法及周期果蝇算法。

In the paper,a novel dichotomy fruit fly optimization algorithm(DFOA)is proposed to improve deployment in WSN,each fruit fly represents a solution for sensor deployment independly.Every fruit fly is divided into two virtual flies at every iteration,then the two flies find their optimal fitness function along different given step length,through iterarions,the global optimal position is achieved,which is also the optimal solution for sensor deployment.The simulation results show that the coverage rate of the DFOA is better than that of FOA,DS-FOA,CS-FOA.