Abstract:Aiming at the shortages of basic dragonfly algorithm with easy to fall into local optimum, slow convergence speed and low search precision, a new algorithm based on random substitution and hybrid mutation (DASM) is proposed. Firstly, chaotic mapping is used to enhance the quality of initial solution. Secondly, a random substitution strategy of the center point is introduced to improve the convergence rate of the algorithm. Finally, in order to jump out of the local optimum and improve the convergence precision, the individual population is mutated. The experimental results show that the proposed algorithm is much better than basic dragonfly algorithm and its several improved algorithms in optimization performance.