基于改进的人工蜂群算法的阵列综合研究

Array Synthesis on the Basis of an Improved Artificial Bee Colony Algorithm

针对人工蜂群算法在解决较复杂优化问题时易陷入局部最优而过早收敛问题,提出了一种改进的人工蜂群算法。从算法的选择机制角度出发,将模拟退火过程引入人工蜂群算法,提升了算法全局搜索能力和优化精度。利用测试函数对算法的性能进行了分析与比较,并将该算法应用于阵列综合,实验结果表明所提算法的优化精度明显高于标准人工蜂群算法,验证了算法在方向图综合中的有效性和可行性。

Aiming at the problem that Artificial Bee Colony(ABC) algorithm is liable to fall into local optimum, an improved ABC algorithm is proposed. Focusing on the selection of algorithm simulated annealing is introduced to the ABC algorithm. In this way precision and search capability of algorithm is improved. This algorithm is applied in bench test functions and its performance is analyzed and compared. Besides the array synthesis of uniform linear array is realized by this method. The simulation results show that the precision of proposed algorithm is much better than the standard ABC and it is effective and feasible in array synthesis application.