Grid Task Scheduling Strategy Based on Differential Evolution-Shuffled Frog Leaping Algorithm

This paper proposes an Differential Evolution-Shuffled Frog Leaping Algorithm (DE-SFLA) for grid task scheduling. For Shuffled Frog Leaping Algorithm search in multi-direction, the frog leaping strategy is optimized, while taking advantage of the Differential Evolution Algorithm to produce better individuals by mutation, crossover and selection. The algorithm combines Differential Evolution Algorithm and Shuffled Frog Leaping Algorithm, effectively enhances the diversity of the population, and overcomes local convergence insufficiency and degradation of Shuffled Frog Leaping Algorithm. Compared with the Genetic Algorithm and Shuffled Frog Leaping Algorithm task scheduling strategy, experiment show that it can reduce the time span of the task scheduling and enhance the performance of grid system effectively.

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