Modeling and Simulation of CMOS Schmitt Trigger Circuits Using a Multi-Objective Mayfly Optimization Algorithm

Abstract

Schmitt Trigger Circuits (STCs) play a crucial role in digital and analog signal processing by providing noise immunity and stable switching behavior. However, optimizing STC performance for low-power, high-speed applications remains a challenging task. This study proposes a novel approach using the Multi-Objective Mayfly Optimization Algorithm (MOMA) to optimize key STC parameters, including power dissipation, propagation delay, and hysteresis voltage. The optimization process was conducted using MATLAB, whereas LTSpice was employed for circuit-level validation using 0.25 μm/2.5 V CMOS technology. To identify the best trade-off solutions, various weighting methods were applied, including Statistical Variance, Standard Deviation, CRITIC, and Mean methods, ensuring a balanced evaluation of circuit performance. Numerical results show that the optimized STC achieved a 23% reduction in propagation delay, a 38% decrease in power dissipation, and improved noise immunity while maintaining robust switching characteristics. These findings confirm the effectiveness of MOMA in designing low-power, high-performance STCs suitable for modern VLSI, biomedical, and IoT applications.