Edge covering problem under hybrid uncertain environments

Edge covering problem (ECP) is to find an edge cover with the minimum weight in a graph. By quantifying costs, time or opponent's payoffs as weights on edges, ECP is employed to model many real-life problems in engineering and management. Since various types of uncertainty always exist in real world, this paper considers ECP under hybrid uncertain environments where randomness and fuzziness coexist. We propose three decision models and present a hybrid intelligent algorithm to solve the proposed models where genetic algorithm and random fuzzy simulation are embedded. Numerical experiments are performed to show the robustness of the proposed algorithm.