An improved crow search algorithm with multi strategy disturbance

As a new meta heuristic intelligent algorithm, crow search algorithm simulates the behavior of crows following each other and stealing food. Due to simplicity robustness it has been successfully applied in many fields. However, like swarm intelligence optimization algorithms, also disadvantages slow convergence speed easy fall into local optimization. In order improve accuracy later ability hybrid called multi strategy disturbance improved (MSD-CSA) is proposed based on traditional algorithm. MSD-CSA, sharing mechanism added location update mode random tracking original reduce blindness speed. addition, global optimal perturbed with different sizes iterative stages, which effectively improves probability jumping out ensures balance between evaluate effectiveness MSD-CSA 20 basic test functions for experiments, compared algorithms. Experimental results show that average are better than overall performance good.