电子科技2024，Vol.37Issue(8)：8-16,25,10.DOI:10.16180/j.cnki.issn1007-7820.2024.08.002
基于对称映射搜索策略的自适应金鹰算法及应用
Adaptive Golden Eagle Algorithm Based on Symmetric Mapping Search Strategy and its Application
摘要
Abstract
The GEO(Golden Eagle Optimizer)is a population-based meta-heuristic algorithm that simulates the cooperative hunting behavior of golden eagles.In view of the problem of poor solution accuracy and local optima traps in the GEO algorithm,this study proposes an improved MERGEO(Mapped Elitist Reverse GEO)algorithm.Based on the original algorithm,symmetric mapping search strategy,adaptive elite strategy and random backward learning mechanism,are used to balance the exploration and development stages of the algorithm,and obtain the a-bility to avoid local optimal and better optimization accuracy.The independent strategy effectiveness analysis,scal-ability analysis and optimization performance comparison with other algorithms are carried out on 10 benchmark test functions.The experimental results show that the improved MERGEO algorithm has strong competitiveness and good optimization ability.The improved algorithm is applied to the coverage optimization problem of wireless sensor net-works and pressure vessel design problem,which verifies the practical application value of improved algorithm.关键词
金鹰优化算法/元启发式算法/对称映射搜索策略/自适应精英策略/随机反向学习/可扩展性分析/无线传感器网络的覆盖优化/压力容器设计Key words
golden eagle optimization algorithm/meta-heuristic algorithm/symmetric mapping search strategy/adaptive elite strategy/stochastic reverse learning/scalability analysis/coverage optimization of wireless sensor net-work/pressure vessel design分类
信息技术与安全科学引用本文复制引用
周徐虎,李世港,罗仪,张伟..基于对称映射搜索策略的自适应金鹰算法及应用[J].电子科技,2024,37(8):8-16,25,10.基金项目
国家自然科学基金(11502145)National Natural Science Foundation of China(11502145) （11502145）
