Comparison of algorithms for optimizing mechanical design reveals strengths for specific objectives.
Key Points
The aim is to compare differential evolution and particle swarm optimization methods for mechanical component design optimization across different objectives.
Compared differential evolution (DE) and particle swarm optimization (PSO) for mechanical component design.
Evaluated algorithms across standardized mechanical design problems with single-objective and multi-objective formulations.
Analyzed convergence behavior and Pareto front quality through hypervolume metrics.
Both DE and PSO achieved solutions equal to or better than existing literature in single-objective cases.
PSO generally offered superior solutions with faster convergence.
MODE produced broader Pareto fronts with higher hypervolume scores compared to MOPSO, which showed good performance but less diversity.