A hybrid self-adaptive evolutionary algorithm for the minimum weight dominating set problem

Abstract

Given an undirected graph with weights associated with its vertices, the minimum weight dominating set problem MWDSP is to determinate a subset of vertices with minimum sum of weights such that each vertex of the graph either belongs to the subset or is adjacent to a vertex in the subset. This paper presents a hybrid self-adaptive evolutionary algorithm for the MWDSP. A greedy randomised adaptive construction procedure is used to generate an initial population. Then, a crossover operator and an adaptive mutation operator are employed to generate a new solution, which is further refined by an adaptive tabu search. These adaptive strategies make a good balance between intensification and diversification. Computational experiments on two types of benchmark instances prove that our proposed algorithm can find high quality solutions in a short computing time.