Applications of the Circle-Inspired Optimization Algorithm: Comparison between MatLab and Python versions

Resumo

This paper presents applications of the Circle Inspired Optimization Algorithm (CIOA), a modern optimization algorithm developed by the authors, in optimization problems from different areas of study implemented in MatLab and Python, with the main objective of making a comparison between versions of each computer language. Different sets of optimization problems were selected, involving classical benchmark functions, traditional truss structural optimization problems, and real-world optimization problems obtained in the 'CEC2020 Real-World One-Objective Constrained Optimization Competition'. Each optimization problem was solved multiple times on the same computer in MatLab and Python, to make comparisons between the accuracy and robustness of each version of the algorithm, evaluating the best solution and the mean and standard deviation between several solutions. Furthermore, a comparison of computational time was also performed. The results obtained attest to the efficiency of CIOA in both computational languages. In terms of accuracy and robustness, it was not possible to clearly identify a better version (MatLab or Python) for CIOA, as the differences obtained in the results were, in most cases, very small, and may be caused by the random characteristics of the algorithm. In the comparison of computational time, the MatLab version performed better in most optimization problems. This fact may be due to the efficiency of the specific libraries used and the programming experience of the authors in each computer language.