Chaos Fusion Mutation-Based INFO Algorithm for Linear Antenna Array Optimization

Abstract—This manuscript introduces the Chaos Fusion Mutation INFO algorithm (CFMINFO), which integrates multiple strategies and updates vector positions through three core processes. These processes incorporate Good Point Set initialization, Sine-Tent-Cosine (STC) chaotic parameterization, and Normal Cloud Mutation strategies. The algorithm is characterized by its simplicity, rapid convergence, and ability to avoid local optima. To validate its performance, CFMINFO is applied to the optimization of linear arrays. Comparisons with other algorithms under various constraints reveal that CFMINFO achieves lower Sidelobe Level (SLL), faster convergence speed, and greater stability in five simulation instances. Furthermore, the final simulation example demonstrates that CFMINFO outperforms the compared Improved Invasive Weed Optimization (IWO) in both reducing deep nulls and minimizing the maximum SLL.