Abstract
The Cauchy distribution optimizer (CDO), a revolutionary nature-inspired metaheuristic method for engineering design, is developed in this study. To prevent early convergence, find a balance between exploration and exploitation in the answer space, CDO method primarily mimics the position parameter and scale parameter behavior of the Cauchy distribution. 29 common CEC2017 unconstrained benchmark functions were used to confirm the CDO’s efficacy and competitiveness. The experimental results show that CDO ranked first overall, with an average ranking of 1.862. Additionally, the approach is applied to five real-world restricted optimization problems including the extraction of solar system key parameters in order to further validate its efficacy. According to the simulation results, the created CDO is a very promising technology that can outperform other cutting-edge competing technologies. The source code for the CDO algorithm is publicly accessible at https://ww2.mathworks.cn/matlabcentral/fileexchange/182811-cauchy-distribution-optimizer.