The choice of method depends on factors such as the complexity of the system, availability of computational resources, desired level of optimization, and familiarity with the optimization technique. For simple systems with known dynamics, heuristic methods like Ziegler-Nichols may suffice. However, for complex or nonlinear systems, metaheuristic optimization algorithms like GA, PSO, ACO, or WOA may offer better performance and convergence properties. Experimentation and comparative analysis can help determine the most suitable method for a particular application.