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The advanced optimization method named as adaptive range differential evolution (ARDE)is developed. The optimization performance of ARDE is demonstrated using a typical mathematical test and compared with the standard genetic algorithm and differential evolution. Combined with parallel ARDE, surface modeling method and Navier-Stokes solution, a new automatic aerodynamic optimization method is presented. A low aspect ratio transonic turbine stage is optimized for the maximization of the isentropic efficiency with forty-one design variables in total. The coarse-grained parallel strategy is applied to accelerate the design process using 15 CPUs. The isentropic efficiency of the optimum design is 1.6% higher than that of the reference design. The aerodynamic performance of the optimal design is much better than that of the reference design.