改进人工蜂鸟算法的无线传感器网络部署优化  

Optimization of Wireless Sensor Network Deployment with Improved Artificial Hummingbird Algorithm

作　　者：张超[1] 杨忆[2] ZHANG Chao;YANG Yi(Department of Computer Information,Suzhou Vocational and Technical College,Suzhou 234101,Anhui,China;College of Computer Science and Technology,Huaibei Normal University,Huaibei 235000,Anhui,China)

机构地区：[1]宿州职业技术学院计算机信息系,安徽宿州234101 [2]淮北师范大学计算机科学与技术学院,安徽淮北235000

出　　处：《江汉大学学报（自然科学版）》2023年第5期75-86,共12页Journal of Jianghan University：Natural Science Edition

基　　金：安徽省高校优秀青年人才支持计划重点项目(gxyqZD2019125);安徽省高校自然科学基金重点项目(2022AH052764,KJ2020A0035);安徽省高等学校省级质量工程项目(2020kfkc577,2020jyxm2226)。

摘　　要：人工蜂鸟算法在求解高维度复杂优化问题时,易陷入局部极小值,导致算法收敛停滞。提出一种改进的人工蜂鸟算法(improved artificial hummingbird algorithm,IAHA),并用其优化无线传感器网络部署。首先对蜂鸟个体和最优蜂鸟之间距离进行正切函数变换,以最优蜂鸟位置为基准,以变换的距离为飞行尺度,提出一种新的觅食策略。其次,在迁徙觅食阶段,使用柯西分布对最优蜂鸟信息进行扰动,将扰动结果赋予最差蜂鸟,取代基本人工蜂鸟算法的随机赋值方法。在12个基准函数上的数值实验表明,IAHA的寻优性能优于6种对比算法。在4种监测区域上进行了无线传感器网络部署优化仿真实验,结果表明,IAHA获得的平均覆盖率高于对比算法,且传感器分布均匀,适合求解无线传感器网络部署优化问题。The artificial hummingbird algorithm is prone to fall into local minima and convergence stagnation when solving high-dimensional complex optimization problems.Therefore,an improved artificial hummingbird algorithm(IAHA)was proposed to optimize wireless sensor network deployment.Firstly,the tangent function transformation of the distance between individual hummingbirds and the optimal hummingbird was performed,and a new foraging strategy was proposed with the optimal hummingbird position as the base and the transformed distance as the flight scale.Secondly,the optimal hummingbird information was perturbed using the Cauchy distribution during the migratory foraging phase,and the perturbation result was assigned to the worst hummingbird,replacing the random assignment method of the original algorithm.Numerical experiments on 12 benchmark functions demonstrated that the IAHA outperformed the six comparison algorithms significantly in terms of finding the best performance.Simulation experiments of wireless sensor network deployment optimization were conducted on four monitoring areas,and the results showed that the average coverage rate obtained by IAHA was higher than that of the comparison algorithm,and the sensors were evenly distributed,which was suitable for solving the wireless sensor network deployment optimization problem.

关 键 词：人工蜂鸟算法 无线传感器网络 柯西分布 正切变换距离 覆盖率 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]