Which AI techniques can you recommend for optimizing reorder points, order sizes with simulation? (Or in general: 6 interdependent parameters with 1 objective value)

I like to work with simulation, and I am looking for some inputs into improvements to my techniques. I will study more machine learning and AI. I have already applied with Optuna (bayesian optimization)

My simulation results. Optimization is performed, but I want to learn other (and better) techniques

(objective value in the picture is the sum of holding, ordering and shortage costs)

Have any of you worked with similar studies? Are the any techniques that you can recommend?

The simulation is fairly simple.
The six variables is inputted and the ends up with a total inventory cost.

I was considering to make the demand of the inventory system stochastic, so that it changes for every time the simulation runs.

Currently the simulation outputs the same objective value if the same set of parametes are inputted, but with stochastic demand that would change.