山东大学学报 (工学版) ›› 2024, Vol. 54 ›› Issue (5): 74-80.doi: 10.6040/j.issn.1672-3961.0.2023.262
王辰龑1,2,刘轩1,2*,超木日力格1,2
WANG Chenyan1,2, LIU Xuan1,2*, Chaomurilige1,2
摘要： 为提高天牛须搜索算法(beetle antennae search algorithm, BAS)寻优能力,提出一种自适应的并行天牛须优化算法(adaptive and parallel beetle antennae optimization algorithm, APBAO),该算法将BAS中的单只迭代体进化为并行的多只迭代体,尽可能扩大解空间的搜索范围;提出精英天牛的概念实现算法自适应,提高算法精度。为验证算法的性能,采用多个标准测试函数进行测试,将APBAO与BAS、粒子群优化算法(particle swarm optimization, PSO)和蚁群优化算法(ant colony optimization, ACO)的性能进行比较。试验结果表明,与BAS相比,APBAO对目标函数的优化率提高了97.39%,与PSO和ACO相比分别提高了84.46%和86.98%。所提出方法可以有效避免目标函数陷入局部最小值,拥有更好的性能和更强的寻优能力。
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