Identifying cohesive subgraphs is an important topic in graph theory and
complex network analysis. The quasi-clique, as a generalization of
clique, can be used to identify functional and structural properties of
various networks. In this paper, we study the maximum weighted
quasi-clique problem, and propose a local search algorithm for solving
the problem. In the algorithm, an iterated local search method is used
as the search framework. To find the quasi-clique with the maximum total
weights, hybrid vertex selection strategies are proposed and
incorporated into our algorithm. The hybrid strategies utilize a
probability-based mechanism for choosing sub-strategies in each round of
the local search. We conduct experiments on synthetic networks and
real-world networks to show the effectiveness of our algorithm. The
results indicate that hybrid strategies perform better than existing
methods, and thus our algorithm has a good ability to tackle various
networks.