Given a social network with diffusion probabilities as edge weights and a positive integer k,
which k nodes should be chosen for initial injection of information to maximize the influence …

We consider opinion diffusion in binary influence networks, where at each step one or more
agents update their opinions so as to be in agreement with the majority of their neighbors …

Modern traceability technologies promise to improve supply chain management by
simplifying recalls, increasing visibility, and verifying sustainable supplier practices …

Identifying the most influential spreaders is an important issue for the study of the dynamics
of information diffusion in complex networks. In this paper we analyze the following …

We consider a population of interconnected individuals that, with respect to a piece of
information, at each time instant can be subdivided into three (time‐dependent) categories …

Given a network represented by a graph G=(V, E) G=(V, E), we consider a dynamical
process of influence diffusion in G that evolves as follows: Initially only the nodes of a given …

Consider a graph G and an initial configuration, where each node is black or white. Assume
that in discrete-time rounds, all nodes simultaneously update their color based on a …

This research proposes the use of metaheuristics for solving the Target Set Selection (TSS)
problem. This problem emerges in the context of influence maximization problems, in which …

The use of machine learning techniques within metaheuristics is a rapidly growing field of
research. In this paper, we show how a deep learning framework can be beneficially used to …

The Target Set Selection (TSS) problem is an NP-hard combinatorial optimization problem
with origins in the field of social networks. There are various problem variants, all dealing …