论文标题
使用Ant Hill定植优化算法（AHCOA）的线性天线阵列的最佳图案合成
Optimal Pattern synthesis of linear antenna array using Ant Hill Colonization Optimization algorithm(AHCOA)
论文作者
论文摘要
本文的目的是向电磁和天线社区介绍Ahcoa。 Ahcoa是一种新的自然启发的元启发式算法，其灵感来自于蚂蚁山殖民化中的等级制度和部门的启发。它具有很高的概率潜力，不仅可以解决不受限制的优化问题。在本文中，AHCOA应用于线性天线阵列，以以下方式进行更好的图案合成：通过均匀的激发考虑天线元件相对于均匀阵列的间距相等。 AHCOA用于获取阵列模式以达到最小的侧叶水平。将结果与其他基于自然的算法（例如Ant Lion Optimizer）进行了比较，蚂蚁狮子优化器显示出可观的AHCOA。
The aim of this paper is to introduce AHCOA to the electromagnetic and antenna community. AHCOA is a new nature inspired meta heuristic algorithm inspired by how there is a hierarchy and departments in the ant hill colonization. It has high probabilistic potential in solving not only unconstrained but also constrained optimization problems. In this paper the AHCOA is applied to linear antenna array for better pattern synthesis in the following ways : By uniform excitation considering equal spacing of the antenna elements with respect to the uniform array. AHCOA is used in obtaining an array pattern to achieve minimum side lobe levels. The results are compared to other state of the art nature based algorithms such as ant lion optimizer, which show a considerable improvement in AHCOA.
