基于改进差分进化算法的Flow Shop调度问题求解

In this paper, a novel Differential Evolution algorithm is presented, which can avoid the premature convergence problem of the traditional Differential Evolution algorithm effectively. The basic principle of the new DE is that chaos initialization is adopted to improve individual quality, the mutation operator and differential strategy adjusted randomly generation by generation, to enhance the searching capacity. Several classic experiments on Flow Shop scheduling problem are tested and the results show that the proposed algorithm can avoid the premature convergence and improves the global convergence ability remarkably.