One is the stability of the model, that is, there are parameters in your model. When you change the range of parameters to a certain extent, the results you get are not much different. If not, the model is stable. For example: y = ax1+bx2; And a+b =1; A and b are weight parameters. When you change the value of a and see how the result changes, this is optimization. Of course, if an algorithm is used, computer simulation is better.

The other is the correctness of the model, that is, the result of your model is correct. You can prove your results in another very simple way, or compare them with other people's research results in the literature you have seen, so as to get the correctness of your results.

I hope I can help you. I am a mathematical modeling enthusiast. I have participated in the national and American competitions of mathematical modeling, and there are many competitions. If interested, you can become friends.