Abstract: An improved differential evolution (IDE) algorithm was proposed for task assignment by modifying two important parameters of DE algorithm: scale factor and crossover rate. The scale factor is adaptively adjusted according to the objective function values of all candidate solution vectors, and the crossover rate is dynamically adjusted with the increasing of iteration steps. The combination of such two parameters is able to not only increase the diversity of candidate solutions but also enhance the develop ability of solution space of the proposed algorithm. Experimental results demonstrated that the IDE algorithm has stronger convergence and higher stability than other three DE algorithms for task assignment.