A novel chaotic dragonfly algorithm based on sine-cosine mechanism for optimization design

Dragonfly algorithm is a novel meta-heuristic algorithm, which solves the problem by simulating the biological behavior of dragonfly's predation and migration. There are also some common problems of meta-heuristic algorithms, such as slow convergence speed and entrapment in local optima. To improve the performance of dragonfly algorithm, this study combines singer chaos and sine-cosine mechanism to reinforce the original dragonfly algorithm. Singer chaos is used to optimize the population initialization of the algorithm, and the sine-cosine mechanism is applied to modify the iterative updating formula of the position. The performance of the proposed approach is examined by eight numerical benchmark functions. From the optimal solution and standard deviation of the experimental data, it can be seen that the convergence accuracy and stability of the proposed dragonfly algorithm are significantly strengthened. Besides, SC-DA is applied to optimize the design of cantilever beam problem with good performance.