A Chaotic Chicken Optimization Algorithm Based on Powell Search

In this paper, a hybrid improved flock optimization algorithm (Powell-LCSO) is proposed to overcome the shortcomings of the traditional flock optimization algorithm (CSO) which is easy to fall into the local extremum and easy to premature convergence. Firstly, the improved algorithm uses Logistic chaotic map to initialize the population, which makes the population better distributed in the solution space. Secondly, the position of the hens in the flocks is improved. Finally, by comparing the Limit threshold to determine whether the algorithm is caught in the local extremum, and using the Powell search to local search for the global optimal individuals, it avoids the premature convergence of the algorithm and improves the accuracy of the algorithm. Its ability to jump out of the local best. Experiments show that the improved flock optimization algorithm has good accuracy and convergence efficiency.