Average convergence rate of evolutionary algorithms in continuous optimization

•Average convergence rate measures the convergence speed of evolutionary algorithms by the geometric average of the reduction rate of the approximation error over consecutive generations.•Evolutionary programming with landscape-invariant or zero landscape-adaptive mutation converges slowly, while that with positive landscape-adaptive mutation converges fast.•Average convergence rate are classified into two types: polynomial or exponential as a function of the decision space dimension.