多策略增强樽海鞘算法下的WSN覆盖优化

WSN coverage optimization under multi-strategy enhanced salp swarm algorithm

为了提高无线传感器网络(wireless sensor network,WSN)的节点覆盖率,提出一种多策略增强的樽海鞘优化算法(enhanced salp swarm algorithm,ESSA)。首先使用Halton序列代替随机序列生成个体的初始化位置,避免随机点之间间隙过大或重叠;其次引入新的非线性收敛因子,加速收敛。最后采用柯西变异机制,增加个体的多样性,促使个体快速跳出局部最优点。将该算法应用到无线传感器网络覆盖优化问题上,并与其他优化方法对比,ESSA表现出更快的收敛速度和更高的覆盖率。

In order to improve the coverage of wireless sensor network(WSN),a multi-strategy enhanced salp swarm algorithm(ESSA)is proposed.Firstly,the initialization position of individuals is generated by using Halton sequences instead of random sequences to avoid the excessive gaps and overlaps between random points.Then,a new nonlinear convergence factor is introduced to accelerate the convergence.Finally,the Cauchy mutation mechanism is integrated to increase the diversity of individuals and promote them to jump out of the local optimal point quickly.The algorithm is applied to the wireless sensor network coverage optimization problem.Compared with other optimization methods,it shows faster convergence speed and higher coverage.