基于改进遗传模拟退火算法的WSN路径优化

针对无线传感器网络路径优化问题,提出了一种改进的最优保存的遗传模拟退火算法。利用LEACH算法构建初始路由表,使用GASA的高效率搜索,将路由计算和遗传演化计算同时进行,并直至寻找到近似最优路径为止。将最优保存遗传算法和模拟退火算法相结合,引入自适应的概率变化,有效地解决了这两种算法的早熟现象和时间问题。仿真实验表明,该算法有效地解决了无线传感器路径优化问题,具有定位准确、节能和搜索能力较强等优点。

WSN path optimization based on the improved genetic simulated annealing algorithm

To resolve the path optimization problem, an improved GASA that adopts adaptive optimal preservation is proposed. It uses LEACH algorithm to construct an initial routing table, uses an efficient search algorithm GASA, therefore the routing calculation and genetic evolutionary computation will executed at the same time, and the path optimization process won’t stop until the approximate optimal path were find. This algorithm combines the maintaining optima saved genetic algorithm and simulated annealing algorithm, and the adaptive probability changes to the mutation, which effectively solves the problem of premature and time. The simulation experiments show that the algorithm effectively solves the routing problem in WSN and has a positioning accuracy, energy and strong ability of searching.