A relevant experience:
We spent a good few months tackling a motor problem where our calculations showed we should have been fine. In the end it turned out that someone had entered an incorrect input in one calculation and the test was far too harsh.
All the time when we were having the problem the test engineers (read “people who have done a lot of iterative optimisation”) were saying it seemed like the test was too harsh. We wasted months trusting too much in the calculations.
Sometimes the main uncertainty is that your model is wrong (or just inadequate) in which case iterative optimisation might win.
A relevant experience: We spent a good few months tackling a motor problem where our calculations showed we should have been fine. In the end it turned out that someone had entered an incorrect input in one calculation and the test was far too harsh. All the time when we were having the problem the test engineers (read “people who have done a lot of iterative optimisation”) were saying it seemed like the test was too harsh. We wasted months trusting too much in the calculations. Sometimes the main uncertainty is that your model is wrong (or just inadequate) in which case iterative optimisation might win.