摘要
蝴蝶优化算法是近年来提出的一种新型自然启发式算法。针对基本蝴蝶优化算法收敛速度慢、求解精度低、稳定性差等问题,提出了一种融合变异策略的自适应蝴蝶优化算法。通过引入动态调整转换概率策略,利用迭代次数和个体适应度的变化信息动态调整转换概率,有效维持了算法全局探索与局部搜索的平衡;通过引入自适应惯性权重策略和局部变异策略,利用惯性权重值和混沌记忆权重因子进一步提高了算法的多样性,有效避免算法早熟收敛,同时加快了算法的收敛速度和求解精度。利用改进算法对12个基准测试函数进行仿真实验,与基本蝴蝶优化算法、粒子群算法、樽海鞘群算法、灰狼优化算法等其他算法对比表明,改进算法具有收敛速度快、寻优精度高、稳定性强等优异性能。
Butterfly optimization algorithm(BOA)is a novel nature-inspired metaheuristics algorithm proposed in recent years.The basic BOA is slow convergence,low accuracy and easy to fall into local optimum.To solve the above problem of basic BOA,this paper proposed an adaptive butterfly optimization algorithm based on mutation strategies(ABOA-MS).Firstly,it introduced the strategy of adjust the conversion probability dynamically,which effectively balanced the ability of the global exploration and local search,by means of dynamically adjusting the switching probability of the change information of iteration times and individual fitness.Secondly,it introduced the adaptive inertia weight strategy and local mutation strategy.It applied the inertia weight value and chaotic memory weight factor,which further improved the diversity of this algorithm,and effectively avoided its precocious convergence,as well as accelerated its convergence speed and solving accuracy.In order to verify the optimization performance of the modified algorithm,it carried out the simulation experiments among the modified algorithm,the basic BOA algorithm,the particle swarm optimization algorithm,the salp swarm algorithm,the gray wolf optimization and the others.Simulation results illustrate that the modified algorithm has excellent performance of fast convergence speed,high optimization accuracy and strong stability.
作者
刘凯
代永强
Liu Kai;Dai Yongqiang(College of Information Science&Technology,Gansu Agricultural University,Lanzhou 730070,China)
出处
《计算机应用研究》
CSCD
北大核心
2022年第1期134-140,145,共8页
Application Research of Computers
基金
甘肃农业大学青年导师基金资助项目(GAU-QDFC-2019-02)
甘肃省高等学校创新能力提升项目(2019A-056)
甘肃农业大学学科建设专项基金资助项目(GAU-XKJS-2018-253)
国家自然科学基金资助项目(61063028,61751313)。
关键词
自然启发式算法
蝴蝶优化算法
自适应惯性权重
变异策略
novel nature-inspired metaheuristics algorithm
butterfly optimization algorithm
adaptive inertia weight
mutation strategy
