A restart local search algorithm with Tabu method for the minimum weighted connected dominating set problem

The minimum weighted connected dominating set problem is a significant NP-hard problem with wide applications, and is an extension of the classical minimum dominating set problem. In order to solve this problem, we present a restart local search algorithm with tabu method (RLS_ Tabu). In our RLS_ Tabu algorithm, we firstly involve the random restart initialization method to jump out of the local optimum. Meanwhile, RLS_ Tabu algorithm also applies tabu method in neighborhood search procedure to mitigate the cycling problem. Secondly, we present two strategies in neighborhood search procedure for removing vertices properly, which one is greedy and random strategy, and another one is multiple deletion strategy. The two strategies are crucial to improve the solution quality. Thirdly, the solution connected vertex is important to guarantee the feasibility of solutions. Therefore, we maintain the solution connected vertex set during the neighborhood search, and select the vertex to be added from this set. Finally, in order to intensify the solution, RLS_ Tabu utilizes the pruning function to delete redundant vertices in the candidate solution. In experimental section, we will compare our algorithm with the other six algorithms on three types of benchmarks. Experimental results indicate that our algorithm significantly outperforms the comparative algorithms on most benchmark instances.