计算机科学 ›› 2024, Vol. 51 ›› Issue (11A): 240100203-7.doi: 10.11896/jsjkx.240100203
任庆欣, 冯锋
REN Qingxin, FENG Feng
摘要： 为解决斑马优化算法易陷入局部寻优、收敛速度慢等一系列问题,提出一种多策略融合改进的斑马优化算法(MSI-ZOA)。首先,利用Tent混沌映射产生随机序列的方式初始化种群,提高初始化种群在搜索空间的分布质量,加强全局探索能力。其次,利用莱维飞行的重尾特性,产生较大步长,增加搜索空间的覆盖率,加强在斑马优化算法(ZOA)的觅食阶段的全局探索能力。接着,使用一种双曲线余弦增强因子的正余弦优化算法,将其应用在ZOA算法的抵御捕食者攻击阶段,以有效挑出局部最优解,提高收敛速度。最后,使用8个基准函数对MSI-ZOA算法、ZOA算法、秃鹰优化算法(AVOA)、人工蜂鸟算法(AHA)、大猩猩部队优化算法(GTO)、算术优化算法(AOA)和北方苍鹰优化算法(NGO)进行测试,结果表明MSI-ZOA算法相比其他6种算法在收敛速度和全局搜索能力上更具优势。
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