吉林大学学报(工学版) ›› 2022, Vol. 52 ›› Issue (8): 1842-1849.doi: 10.13229/j.cnki.jdxbgxb20210170
• 计算机科学与技术 • 上一篇
Ren-chu GUAN1(),Bao-run HE1,Yan-chun LIANG1,2,Xiao-hu SHI1()
摘要:
针对传统粒子群优化算法在解决最优化问题中存在早熟收敛和无法寻找到全局最优解问题,本文提出了一种基于亲缘关系选择的粒子群优化算法,提高了算法的全局搜索能力。此外,引入了多个种群的交流机制与各子种群之间的淘汰机制,有效避免了个体在寻优过程中陷入局部最优点。实验部分首先在单目标优化函数集上与传统的粒子群优化算法以及一些有竞争力的算法结果进行对比分析,发现算法在相同种群规模与评价次数的条件下,在准确性与搜索能力上有着明显的优势;然后,将新算法应用到桁架穹顶优化问题上,并与传统的粒子群优化算法进行了比较,求得了这一实际问题的一个可行解。
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