摘要
针对人工大猩猩部队优化算法(GTO)存在易陷入局部最优、收敛速度慢、寻优精度低等问题,提出了基于双重随机扰动策略的人工大猩猩部队优化算法(DGTO)。引入Halton序列初始化种群,增加种群的多样性;在算法寻优阶段使用多维随机数策略,并在探索阶段提出自适应位置搜索机制,提高算法的收敛速度;提出双重随机扰动策略,解决大猩猩的群居效应,增强算法跳出局部最优的能力;采用逐维更新策略更新个体位置,提升算法的收敛精度。通过10个基准测试函数寻优结果及Wilcoxon秩和检验对比可知,改进算法在寻优精度、收敛速度上有较大提升。同时,通过工程优化问题的实验对比分析,进一步验证了改进算法在处理现实工程问题上的优越性。
Traditional artificial gorilla troops optimizer(GTO)has the drawbacks of easily falling into local optimum,slow convergence speed,and low optimization accuracy.Aiming at these problems,an artificial gorilla troops optimizer based on a double random disturbance strategy(DGTO)was proposed.Firstly,the Halton sequence was introduced to initialize the population to increase the diversity of the population.Secondly,the method’s convergence speed was increased by using the multi-dimensional random number technique during the algorithm optimization stage and proposing an adaptive position exploration mechanism.Thirdly,a double random disturbance strategy was proposed,which solved the group effect of gorillas and enhanced the ability of the algorithm to jump out of the local optimum.Finally,the individual position was updated by a dimension-by-dimension update strategy,which improved the convergence accuracy of the algorithm.It is evident that the enhanced technique has a greater improvement in optimization accuracy and convergence speed when comparing the Wilcoxon rank sum test results with the optimization results of ten benchmark test functions.In addition,through the experimental comparative analysis of one practical engineering optimization problem,the superiority of the proposed algorithm in dealing with practical engineering problems is further verified.
作者
杜晓昕
郝田茹
王波
王振飞
张剑飞
金梅
DU Xiaoxin;HAO Tianru;WANG Bo;WANG Zhenfei;ZHANG Jianfei;JIN Mei(College of Computer and Control Engineering,Qiqihar University,Qiqihar 161006,China;Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis,Qiqihar University,Qiqihar 161006,China)
出处
《北京航空航天大学学报》
北大核心
2025年第6期1882-1896,共15页
Journal of Beijing University of Aeronautics and Astronautics
基金
黑龙江省省属高等学校基本科研业务费自然科学类青年创新人才项目(145209206)。
关键词
人工大猩猩部队优化算法
Halton序列
自适应位置搜索
双重随机扰动策略
逐维更新
artificial gorilla troops optimizer
Halton sequence
adaptive position exploration
double random disturbance strategy
dimension-by-dimension update
作者简介
通信作者:杜晓昕.E-mail:xiaoxindu@qqhru.edu.cn。
