基于遗传算法的移动传感节点路径规划策略研究

Research on Mobile Sensor Node Path Planning Strategy Based on Genetic Algorithm

传统的遗传算法在解决移动节点路径规划问题时由于其算法复杂度高、迭代时间长,容易陷入局部最优。为此,提出一种基于走点法的改进遗传算法。将障碍物凸化处理,从起点出发逐个搜索凸多边形顶点直至目标点,得到有序遗传基因点列后进行初始化处理,以获得连通的初始种群,并逐步采用选择、交叉、变异进行迭代,以得到优化路径。仿真结果表明,该优化策略能减少感知节点路径,缩短初始化与迭代的时间,降低移动节点能耗,提高无线传感网络生命周期。

The traditional Genetic Algorithm（GA） is questioned in solving the problem of mobile node path planning because of its high complexity,long iteration time and easiness to fall into the local optimum. For this reason, this paper proposes an improved GA based on walking point. It turns obstacles into convex polygon, then starts from the starting point and searches for convex polygon vertex until the target point. It then initializes this obtained sequence of genetic genes to obtain initial population. The iterations of selection, crossover and mutation are adopted step by step, and the optimized path is obtained. Simulation results show that the proposed strategy can reduce the path of sensor nodes, shorten the initialization and iteration time, reduce the energy consumption of mobile node and improve the life cycle of Wireless Sensor Network （WSN）.