GRASP for connected dominating set problems

Abstract

The minimum connected dominating set problem, a variant of the classical minimum dominating set problem, is a very significant NP-hard combinatorial optimization problem with a number of applications. To address this problem, a greedy randomized adaptive search procedure (GRASP) that incorporates a novel local search procedure based on greedy function and tabu strategy is proposed. Firstly, the greedy function is proposed to define the score of each vertex so that our algorithm could obtain different possible optimal solutions. Secondly, a tabu strategy is introduced to prevent the search trapping into the local minimum and avoid the cycling problems. The proposed algorithm is evaluated against several state-of-art algorithms on a large collection of benchmark instances. The experimental results prove that GRASP performs better than its competitors in most benchmark instances.