关键词: 4G建站模型, 进化多目标算法, 重点区域, 非重点区域, 极大极小方法

Abstract: 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.

Key words: 4G radio network planning, multiobjective evolutionary algorithm, key area; , nonkey area, minimax methods