Hiding Structure of Reconstructed Network from Subgraphs Using Evolutionary Multi-Objective Optimization

This study considered the problem of reconstructing an overall graph from multiple partially disclosed subgraphs such as supply chains and social networks. Modifying a part of a subgraph can make grasping the structure of the overall graph a challenge, thereby reducing the possibility of identifying essential nodes. However, there is a trade-off between the accuracy of modified subgraphs and the difficulty of grasping the overall structure. We formulated this as a multi-objective optimization problem and investigated its characteristics and the performance of the search operators using evolutionary multi-objective optimization and synthetic problems.