基于分解多目标进化算法的动态可重叠社区发现

ommunity discovery is an important part of network research. With the development of the dynamic and complex Internet, the overlapping community discovery of dynamic network becomes more and more important. In this paper, the Decomposition-Based Multiobjective Evolutionary Algorithm MOEA / D is used to realize the overlapping community discovery of dynamic network. The algorithm has high accuracy and excellent operation efficiency. An improved coding scheme based on adjacent trajectory representation is used to express overlapping community parts and non-overlapping community parts simultaneously. In this algorithm, the community discovery results are generated at the previous time and the initial solution is found at the next time to improve the efficiency of the algorithm, and to ensure the relevance of the findings of the time-slice community.