Negative learning ant colony optimization for the minimum positive influence dominating set problem
Albert López Serrano, Teddy Nurcahyadi, Salim Bouamama, Christian Blum · Proceedings of the Genetic and Evolutionary Computation Conference Companion · 2021
Recent research has shown that adding negative learning to ant colony optimization, in addition to the traditional positive learning mechanism, may improve the algorithms' performance significantly. In this paper we consider the application of this novel ant colony optimization variant to an NP-hard combinatorial optimization problem known as the minimum positive influence dominating set problem. This problem has applications especially in the context of social networks. Our results show, first, that the negative learning variant significantly improves over the standard ant colony optimization variant. Second, the obtained results show that our algorithm outperforms all competitors from the literature.