A multi-objective evolutionary algorithm for hybridization and mutation in key areas is proposed. The proposed algorithm can effectively reduce the length and the complexity of coding when chromosome is in hybridization and mutation

which significantly improves the performance of the multi-objective evolutionary algorithm for 4G radio network model. After the hybridization and mutation

the non-key area was searched again according to the constraint conditions. Then

the candidate base station(BS) was activated

which maximally covered the uncovered test points in non-key areas until the coverage of all the activated BS satisfied the coverage constraint of the model by such analogy. In this way

all the generated solutions were efficient. Moreover

as many test points as possible were covered under the conditions that the activated BS was as little as possible. Finally

a group of optimal solution set was obtained by using the minimax methods. Simulation results have shown the effectiveness of the proposed algorithm.