In my research, I do a black-box optimization based on a simulation model with nonlinear properties. The simulation model gets an operation plan for a time period and then returns a time series, which is evaluated in the fitness function of the algorithms. There are several local minima in the state space. For optimization, I use heuristic algorithms like Particle Swarm Optimization (PSO) or Simulated Annealing (SA).
For this optimization problem, I have already written several papers and each time the reviewers mention why I don't use methods like Mixed integer linear programming, dynamic programming, quadratic programming, etc.
So far, I have assumed that these mathematical methods do not make sense in my case. How do you see this?