To improve the diversity and performance of the Mayfly Algorithm (MA),
this letter adopts the mutation strategies in the process of MA. The
opposition-based learning (OBL) and Cauchy mutation strategies are used
to mutate the global optimal solution, and the artificial mutation
operator is used in the offspring population. The hybrid mutation
strategies are used in a cascaded structure. The performance of the
proposed algorithms is demonstrated in simulations comparatively.