计算机科学 ›› 2020, Vol. 47 ›› Issue (8): 284-290.doi: 10.11896/jsjkx.190700082
张清琪, 刘漫丹
ZHANG Qing-qi, LIU Man-dan
摘要: 社区结构作为复杂网络的重要特性, 对理解网络的功能和结构具有重要意义。为了解决复杂网络的社区发现问题, 提出了一种多目标五行环优化算法(Multi-Objective Five-Elements Cycle Optimization, MOFECO)。首先, 将社区发现问题建模为多目标优化问题, 选取反比率关联(Inverse Ratio Association, IRA)和比例缩减(Ratio Cut, RC)这两个互相对立的目标作为目标函数;然后, 基于五行环模型(Five-Elements Cycle Model, FECM), 通过局部最优解和全局最优解实现元素的更新, 并引入交叉和变异算子对更新策略进行改进;最后, 使用快速非支配排序的方法获得Pareto最优社区划分集合, 有助于揭示复杂网络的层次结构。在人工合成网络和真实社会网络上进行实验, 与单目标算法(GA-Net, Meme-Net)以及多目标算法(MOGA-Net, MOCD, MOEA/D-Net, DMOPSO, DIM-MOEA/D, MOCD-ACO)进行对比得出, MOFECO算法弥补了传统单目标优化社区结构划分单一的缺陷, 在社区发现的准确度上有所提高。
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