Abstract: This paper describes simplex hybrid genetic algorithm called SM-HGA⁺.In detail，by analyzing Neld Meld Simplex algorithm，the authors propose simplex crossover operator and K-step random simplex search operator，and respectively fuse Neld Mead Simplex algorithm and above two novel operators into the best population μP_B（t），the worst population μP_W（t） and a common population P_C（t） in a genetic algorithm in order to construct algorithm SM-HGA⁺.Neld Mead Simplex algorithm in μP_B（t） raises the computation precision；the simplex crossover operator in μP_W（t） accelerates the worst individuals evolving towards better individuals；the K-step random simplex search operator enhances the global convergence speed and genetic algorithm with big crossover probability improves global search performance of algorithm SM-HGA⁺ by population P_C（t）.The standard testing functions test and verify the correctness and efficiency of SM-HGA⁺.