混合遗传算法在WSNs定位中的应用

定位是无线传感器网络(WSNs)的应用支撑,针对用最小二乘法处理DV—Hop算法第三阶段误差过大、定位精度差的问题,提出了遗传算法(GA)+单纯形法的混合GA后期优化处理DV—Hop算法。其中,DV—Hop定位算法第一,二阶段用跳距估计出信标节点与未知节点间的距离,再用GA(建立了代价函数与惩罚函数结合的适应度函数)与单纯形法(作为遗传算子增加了算法的局部搜索能力)结合的混合GA采用保优原则优化未知节点的坐标。通过仿真可知:该算法的定位精度高、网络覆盖率大,适合WSNs的定位。

Application of hybrid genetic algorithm in WSNs localization

Positioning is the application support of wireless sensor networks（WSNs）.To deal with the problem that when using least squares DV-Hop algorithm the third phase error is too large and positioning precision is poor,hybrid genetic algorithm of genetic algorithm （GA） plus simplex method is put forward for later stage optimization processing of DV-Hop algorithm.Among them,the DV-Hop localization algorithm estimates the distance between the unknown node and beacon node with jump in the first and second phase,then,it uses hybrid GA which combines GA set up a fitness function which combines cost function with penalty function with simplex method（increase the local search ability of the algorithm as a genetic operator） to optimize the coordinates of the unknown node according to the optimal principle.Through the simulation,the localization precision of the algorithm is high and its network coverage is large,so it＇ s suitable for localization of WSNs.