A restart local search algorithm with Tabu method for the minimum weighted connected dominating set problem
针对最小权重连通支配集这一NP难问题，提出一种结合随机重启和禁忌搜索的局部搜索算法，通过两种删除策略和连通顶点集维护来提升解的质量，实验表明在多数基准实例上优于对比算法。
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.