A chaotic arithmetic optimization algorithm with Cauchy perturbation and differential evolution for engineering design problems.

Although the arithmetic optimization algorithm (AOA) shows promising performance, it tends to suffer from premature convergence and poor scalability in high-dimensional problems. To address these challenges, we propose the Chaotic Differential Arithmetic Optimization Algorithm (CDAOA), which combines an improved Tent chaotic map for initializing a diverse population, Cauchy perturbation for enhanced exploration, and differential evolution with Lévy flight to strengthen exploitation. CDAOA is benchmarked on 16 classical functions, the CEC 2019 and 2021 test suites, and five real-world engineering problems. Results demonstrate that CDAOA achieves superior performance compared to AOA and several state-of-the-art algorithms in terms of convergence speed and solution quality.