Minimum weight covering problems in stochastic environments

Minimum weight covering problems have played an important role in many real applications. In this paper, two typical minimum weight covering problems, namely vertex covering problem and edge covering problem, are studied under stochastic environments. According to different decision criteria, we propose three stochastic programming models: the expected minimum weight cover model, αα-minimum weight cover model and the most minimum weight cover model. A hybrid intelligent algorithm that integrates stochastic simulation with genetic algorithm is designed to solve the proposed models. Finally, numerical experiments are performed to show the effectiveness and robustness of the proposed algorithm.