In recent years, there has been a notable surge in research on machine learning techniques
for combinatorial optimization. It has been shown that learning-based methods outperform …

Cascading failures are a critical factor affecting the reliability of industrial Internet of things
(IIoT) systems. Establishing a realistic cascading failure model is of significant importance for …

Influence maximization (IM) is a key issue in network science. However, previous research
on IM has previously explored binary interaction relationship in ordinary graphs, with little …

In recent years, one of the prominent research areas in the complex network field has been
the Influence Maximization Problem. This problem focuses on selecting seed sets to achieve …

Multi-Task Evolutionary Optimization (MTEO), an important field focusing on addressing
complex problems through optimizing multiple tasks simultaneously, has attracted much …

Multi-objective evolutionary algorithms have shown their competitiveness in solving ROC
convex hull maximization. However, due to “the curse of dimensionality”, few of them focus …

While link redundancy has long been acknowledged as a critical factor in network
robustness, current approaches frequently neglect the inherent heterogeneity of structure …

Influence maximization (IM) is a critical aspect of complex network analysis, as it holds
considerable commercial value across various domains such as recommendation systems …

Network systems form the foundation of modern society, playing a critical role in various
applications. However, these systems are at significant risk of being adversely affected by …

Influence Maximization (IM) is a critical problem in social network analysis and marketing. It
involves identifying a subset of nodes in a social network whose activation or influence can …