Comparison of algorithms for near-optimal dominating sets computation in real-world networks

Abstract

Computation of the minimum dominating set problem is a classical discrete optimization problem in graph theory. Recently, it has found application in the network controlling theory. In this paper, there are compared three approaches of small dominating set computation. The first one is based on the integer linear programming. The second one is the combined hill-climbing algorithm which is based on the randomization and binary searching. Both are compared with a simply greedy algorithm. The experiments were conducted for three different graph classes. The integer linear programming achieved the best performance for the large real-world network's analysis.