太赫兹科学与电子信息学报2024，Vol.22Issue(11)：1244-1252,1269,10.DOI:10.11805/TKYDA2023383
基于CoMOPSO的传感器优化部署方法
A sensor optimization deployment method based on Collaborative evolution Multi-Objective Particle Swarm Optimization
摘要
Abstract
The sensor optimization deployment is a multi-objective optimization problem involving sensor coverage effectiveness,frequency conflict probability,and resource utilization.The existing sensor optimization deployment methods mostly adopt weighted approaches to transform multiple optimization objectives into a single objective problem for resolution,which not only relies on prior knowledge but also leads to the loss of diversity in optimal solutions.To address these issues,a Collaborative evolution Multi-Objective Particle Swarm Optimization(CoMOPSO)algorithm is proposed.It designs a collaborative evolution framework that guarantees the convergence of high-dimensional problems through the convergence of the population,and rapidly approaches the Pareto optimal frontier.The diverse population uses the ∈-dominance method to ensure the integrity and diversity of the global and local optimal solution sets.A fast non-dominated sorting and elite individual preservation strategy is employed to enhance the quality of solutions.Experimental results demonstrate that,for the sensor optimization deployment problem,the proposed method outperforms traditional optimization algorithms in terms of Inverted Generational Distance(IGD)and M *3 indicators,exhibiting better convergence and diversity and effectively improving the performance of sensor networks.关键词
传感器/优化部署/多目标优化/粒子群/协同进化Key words
sensor/optimization deployment/multi-objective optimization/particle swarm/collaborative evolution分类
信息技术与安全科学引用本文复制引用
张玉翔,郭兰图,刘玉超..基于CoMOPSO的传感器优化部署方法[J].太赫兹科学与电子信息学报,2024,22(11):1244-1252,1269,10.基金项目
国家自然科学基金资助项目(U20B2038) （U20B2038）
