An improved meta-heuristic optimization algorithm based on chaotic mapping inspired by the football team training

Aiming at the shortcomings of the football team training algorithm (FTTA) that the solution is unstable and easy to fall into local optimum, this paper proposes 15 kinds of chaotic mappings to initialize the player population to improve the football team training algorithm, starting from the collective training of FTTA. Finally, the performance of the 15 improved soccer team training algorithms is verified by CEC2020 test function F1 and compared with the initial soccer team training algorithm. In the test, Sinusoidal map improved FTTA showed better performance. It provides new ideas and directions for improving FTTA.