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提出了一种新的同时对共形阵非均匀子阵分区和子阵幅度激励进行优化的多目标进化算法,为此设计了新的多目标函数,通过在改进的强度Pareto进化算法(SPEA2)使用克隆选择算子和双交换遗传操作算子,从而提高搜索效率和收敛性,可以有效改善整个阵列的辐射特性.在系统仿真中,结合工程化实际应用,本文提出的MOEA算法对20*20阵列进行非均匀子阵分区和对各个子阵的幅度激励优化,仿真结果表明其天线阵列在扫描空域的峰值旁瓣电平(PSLL)以及方位和俯仰波束宽度等性能参数得到明显改善,该方法对改善整个阵列的辐射特性是有效的.“,”A novel method for improving multi-objective evolutionary algorithms is described in the paper, which can simultaneously optimize nonuniform conformal subarrays partitions and conformal subarrays amplitude excitation. For the purpose, the new multi-objective functions have been designed, double alternative genetic operator in the improved strength Pareto evolutionary algorithm (SPEA2) is used to improve searching efficiency and convergence and radiant characteristic of the whole array. In system simulation, considering project application, the proposed algorithm is employed to divide a 20*20 array into 25 nonuniform subarrays and each subarray amplitude excitation is optimized. Simulation results show that the performance of peak sidelobe level (PSLL) and beamwidth in azimuth and elevation of antenna array in scan airspace is improved greatly. It has been proved that this is effective for this algorithm to improve radiant characteristic of the whole array