Abstract: Aiming at  the problem of low solution precision in existing optimization algorithms, we proposed a global-local cooperative optimization algorithm with fitness step size.  The algorithm achieved  effective collaboration between global and local search in  the solution space by balancing  individual fitness and dynamically allocating global and local search step sizes during each iteration, thereby enhancing the solution precision. Experimental results show that  the proposed algorithm has  high precision and stability in benchmark function tests, and its effectiveness in solving complex engineering optimization problems is verified through simulation experiments.

Key words: optimization algorithm, normalized fitness value, fitness step size, cooperative search, engineering optimization