A power optimization approach for mixed polarity Reed–Muller logic circuits based on multi-strategy fusion memetic algorithm

• MFMA integrates chimp optimization and coati optimization with adaptive weight factor to balance global and local search, overcoming slow convergence and local optima pitfalls. • Achieves a maximum power saving rate of 72.30% and an average optimization rate of 43.37% on MCNC benchmark circuits, significantly outperforming existing methods. • Provides a robust and efficient solution to the combinatorial explosion in MPRM polarity search, enabling faster convergence and higher-quality solutions. • Establishes a practical framework for low-power IC design, with implications for portable devices and heat-dissipation cost reduction.