An Improved Greedy Heuristic for the Minimum Positive Influence Dominating Set Problem in Social Networks

This paper presents a performance comparison of greedy heuristics for recent variant the dominating set problem known as minimum positive influence (MPIDS) problem. APX-hard combinatorial optimization has applications in social networks. Its aim is to identify small subset key influential individuals order facilitate spread whole network. In this paper, we focus on development fast and effective heuristic MPIDS problem, because are an essential component more sophisticated metaheuristics. Thus, well-working supports efficient Extensive experiments conducted wide range networks complex confirm overall superiority our algorithm over its competitors, especially when size becomes large. Moreover, compare with integer linear programming solver CPLEX. While CPLEX very strong medium-sized networks, it reaches limits being applied largest However, even context only 2.53% worse than