Marine Predators Algorithm Based on Trigonometric Function

In the Marine Predators Algorithm (MPA), a set of solutions is randomly generated in a given search space and the optimal solution is searched through an iterative process, although MPA has shown good performance, it has not solved the problem of local optimal solutions and premature convergence caused by insufficient iterations of the search agent, and its optimization performance still has a lot of room for exploration. Therefore, this paper proposes a trigonometric function-based MPA (TF-MPA) algorithm. First, the trigonometric function is used to optimize the position update of the prey matrix; then the cosine function is used to define the inertia weight coefficient; finally, the sine function is used to define the nonlinear step size control parameters. The effectiveness of TF-MPA is tested on nine standard test functions, and the results show that the TF-MPA algorithm has faster convergence speed and higher stability than the traditional MPA algorithm and other improved algorithms. This proves the effectiveness of the algorithm.