一种基于遗传算法与蚁群算法混合算法的无线传感器网络定位算法

A Hybrid Algorithm Based on Genetic Algorithm and Ant Colony Algorithm for Wireless Network Location

无线传感器网络技术应用广泛,而大多数应用依赖于节点定位,本文提出了一种基于遗传算法与蚁群算法混合算法的节点定位算法,遗传算法采用实数编码,利用线性交叉和非均匀变异算子进行搜索,在遗传算法搜索结果的基础上,利用改进的蚁群算法进行进一步搜索,蚁群算法采用MMAS算法,根据遗传算法搜索结果产生初始吸引强度分布,之后应用精英策略比较混合算法产生的新个体与父代种群,保留较优个体为新一代种群。仿真结果表明,混合算法的定位精度优于dv-hop,遗传算法等传统定位算法,算法收敛性也优于遗传算法和蚁群算法,该混合算法汲取了两种算法的优点,时间效率高,定位精度高,收敛速度快,是一种优秀的无线传感器网络定位算法。

Wireless sensor network technology is widely used, and most applications rely on node localization. In this paper, a hybrid algorithm based on genetic algorithm and ant colony algorithm is proposed. The genetic algorithm uses real-coded, linear and non-uniform mutation operator.Based on the search results of genetic algorithm, an improved ant colony algorithm is used to search further. The ant colony algorithm uses MMAS algorithm to generate the initial attraction intensity distribution according to the genetic algorithm search result, and then applies the elite strategy to compare the new individuals and parental population, and the individuals with better fitness were the new generation.The simulation results show that localization precision of the hybrid algorithm is better than the traditional localization algorithm such as dv-hop and genetic algorithm, and the convergence of the algorithm is better than that of the genetic algorithm and ant colony algorithm. The hybrid algorithm has the advantages of two algorithms, High positioning accuracy,fast convergence speed, is an excellent wireless sensor network localization algorithm.