A Comprehensive Comparative Study of Evolutionary, Swarm Intelligence, and Physics/Mathematics-Based Optimization Algorithms by the Novel SRA Algorithm

Key Points

• The novel SRA algorithm outperforms traditional optimization algorithms in efficiency and accuracy.
• Performance metrics indicate that SRA showed a 15% improvement over leading evolutionary algorithms on complex problems.
• Method assessed encompassed various optimization approaches including swarm intelligence and physics-based models.
• Results encourage further exploration of the SRA algorithm to enhance optimization tasks across disciplines.