计算机科学 ›› 2021, Vol. 48 ›› Issue (7): 270-280.doi: 10.11896/jsjkx.200800087
石克翔, 保利勇, 丁洪伟, 官铮, 赵雷
SHI Ke-xiang, BAO Li-yong, DING Hong-wei, GUAN Zheng, ZHAO Lei
摘要： 为了优化与初始蜜源和搜索方式相关的时间序列分布,从而提高算法全局开拓性和遍历寻优效率,提出一种基于生成时间序列均匀优化的混沌人工蜂群算法。针对混沌时间序列生成的初始蜜源的分布过于集中的问题,首先依据最大熵原理,对Logistic混沌映射进行均匀化优化,并运用熵谱分析以及NIST随机性测试的方法验证其随机程度,使得由其生成的初始蜜源可以随机且均匀地分布在整个解空间,为算法的全局寻优奠定基础;其次,依据由近及远的搜索策略,改进邻域搜索方式,利用均匀化时间序列查找蜜源最优位置,提高算法的遍历速度和收敛精度;最后,所提算法对9个标准测试函数进行了实验仿真,并与其他改进人工蜂群算法和优化算法从收敛曲线和寻优结果上进行了综合比较,进而将6种算法合理引入到物流配送问题中以寻找最短路径。实验结果表明,所提优化算法不仅加强了初始蜜源的均匀性,而且优化效果更为显著,能跳出局部最优且能准确快速地找到全局最优解。
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