A Selected Differential Shuffled Frog Leaping Algorithm (SDSFLA) is proposed. Compared with the classic Shuffled Frog Leaping Algorithm (SFLA), SDSFLA improves the efficiency of populationupdatingby increasingthe number of updated vectors, uses thecrossover operator and mutation operator of Differential Evolution(DE) to strengthen information exchanges between vectors, uses multiple updating strategies to improve the success rate of the trial vectors, and increases the diversity of the population viarandomly-selected control parameters.Based on 16 benchmark functions, SDSFLA is compared with an improved frog leaping algorithm and two improved differential evolution algorithms. The test results confirm the validity and stability of the SDSFLA algorithm.