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Article History

Received: 12 August 2024

Accepted: 23 April 2025

First Online: 28 May 2025

Declarations

:

: The authors declare that they have no conflict of interest.

: All the presented methodology is implemented in Matlab and Python, utilizing the finite element software ANSYS for the numerical modeling and simulations. The specific code versions, executable scripts, parameter settings, and result files for the optimization algorithms—Genetic Algorithm (NSGA-II), Particle Swarm Optimization (MOPSO), Sunflower Optimization (MOSFO), and Lichtenberg Algorithm (MOLA)—are integrated and executed through interactions between Matlab and ANSYS APDL. The experimental methodologies involving the 3D printing of tire prototypes and their compression testing procedures are detailed in the manuscript to ensure accuracy in replication. These procedures include specifications of the 3D printer model, material type (PLA filament), and settings for the compression tests using an Instron universal testing machine. All software scripts, including those for parametric studies and optimization as well as the complete set of raw data files from simulations and experimental tests, are available from the corresponding author upon request. This includes detailed configurations necessary to replicate the findings and to facilitate further research and verification by the academic and industrial communities involved in tire technology and optimization studies.