基于遗传PSO的无线传感网络覆盖优化算法研究

Based on Genetic PSO Wireless Sensor Network Coverage Optimization Algorithms

针对基于标准粒子群算法的网络覆盖存在收敛速度慢、易早熟等问题,提出一种基于遗传PSO的无线传感网络覆盖优化算法.以无线传感器最大覆盖率为目标函数,通过运用加入自适应交叉变异因子的遗传算法搜索解空间,利用PSO粒子群强大的全局搜索能力加大搜索范围,使粒子覆盖更有效率,加强算法的寻优能力,提高节点的覆盖率,解决早熟问题.仿真实验表明,与传统遗传算法、新量子遗传算法相比,其覆盖率分别提高了2.28%和0.65%,收敛速度也有所提高,因此该方法能有效地实现无线传感网络覆盖优化.

According to the standard particle swarm algorithm based on the existing network cover slow convergence speed, easy early, is proposed based on the genetic PSO of wireless sensor network coverage optimization algorithm. In wireless sensor maximum coverage as the objective function, through the application of join adaptive crossover and mutation factor genetic algorithm to search the solution space, using the PSO （particle swarm optimization） powerful global search ability increase search scope, make particle cover more efficient, strengthen algorithm optimization ability, improve the node coverage, solve premature problem. Simulation results show that, with the standard traditional genetic algorithm, the PSO algorithm optimization results were compared, and the coverage increased by 2. 28% and 0. 65%respectively; and convergence speed increased, so this method can effectively realize the wireless sensor network coverage optimization.