The Firefly Algorithm (FA), while effective for complex optimization, suffers from inherent limitations such as search oscillation and low convergence precision. To address these issues, a firefly algorithm with multiple learning ability based on gender difference (MLFA-GD) is proposed. Firstly, the algorithm evenly divides the randomly initialized population into male and female subgroups. Then a male firefly learning strategy which incorporated a partial attraction model combining with an escape mechanism, and a…