Multi-Topology Hierarchical Collaborative Hybrid Particle Swarm Optimization Algorithm for WSN  

作　　者：Yi Wang Kanqi Wang Maosheng Zhang Hongzhi Zheng Hui Zhang 

机构地区：[1]School of Information Science&Technology,Northwestern University,Xi’an 710127,China [2]Institute of Artificial Intelligence,Xiamen University,Xiamen 361102,China [3]Institute of Disaster Prevention and Ecological Restoration,Xi’an Jiaotong University,Xi’an 710054,China

出　　处：《China Communications》2023年第8期254-275,共22页中国通信（英文版）

基　　金：supported by the National Key Research and Development Program Projects of China(No.2018YFC1504705);the National Natural Science Foundation of China(No.61731015);the Major instrument special project of National Natural Science Foundation of China(No.42027806);the Key Research and Development Program of Shaanxi(No.2022GY-331)。

摘　　要：Wireless sensor networks(WSN)are widely used in many situations,but the disordered and random deployment mode will waste a lot of sensor resources.This paper proposes a multi-topology hierarchical collaborative particle swarm optimization(MHCHPSO)to optimize sensor deployment location and improve the coverage of WSN.MHCHPSO divides the population into three types topology:diversity topology for global exploration,fast convergence topology for local development,and collaboration topology for exploration and development.All topologies are optimized in parallel to overcome the precocious convergence of PSO.This paper compares with various heuristic algorithms at CEC 2013,CEC 2015,and CEC 2017.The experimental results show that MHCHPSO outperforms the comparison algorithms.In addition,MHCHPSO is applied to the WSN localization optimization,and the experimental results confirm the optimization ability of MHCHPSO in practical engineering problems.

关 键 词：particle swarm optimizer levy flight multi-topology hierarchical collaborative framework lamarckian learning intuitive fuzzy entropy wireless sensor network 

分 类 号：TP212.9[自动化与计算机技术—检测技术与自动化装置] TN929.5[自动化与计算机技术—控制科学与工程]