计算机技术与发展Issue(1)：53-57,64,6.DOI:10.3969/j.issn.1673-629X.2016.01.011
基于 Memetic 算法的多目标复杂网络社区检测
Multi-objective Complex Network Community Detection Based on Memetic Algorithm
摘要
Abstract
The complex network community detection mechanism was studied and a multi - objective community detection based on Memetic algorithm was presented. In order to improve the diversity of the population,reduce the search space and raise the efficiency of the algorithm,the initialization strategy of label heuristic fast propagation and hybrid crossover were used in the algorithm and a node was selected in each community for mutation to optimize two objective functions,namely Improved Ratio Association (IRA) and Ratio Cut (RC),which turns the multi-objective optimization problem into minimal optimization of these two objectives at the same time. In local search,the local optimization target is constituted of weights of two objective functions and a hill-climbing strategy is used to find the best individual. Experiments on computer-generated networks and two classic real networks show that compared with four algorithms based on EAs and fast modularity algorithm,multi-objective community detection based on Memetic algorithm has certain advantages in solving complex network community detection problem.关键词
Memetic 算法/混合交叉/局部搜索/多目标/网络社区检测Key words
Memetic algorithm/hybrid crossover/local search/multi-objective/network community detection分类
信息技术与安全科学引用本文复制引用
周春霞,周井泉,常瑞云..基于 Memetic 算法的多目标复杂网络社区检测[J].计算机技术与发展,2016,(1):53-57,64,6.基金项目
国家自然科学基金资助项目(61003237,61401225) （61003237,61401225）
江苏省自然科学基金(BK20140894) （BK20140894）
