While the search process benefits from the use of constraints and tight bounds, performance generally suffers when you include requirements in the optimization model for two reasons:
Requirements are very time-consuming to evaluate, since OptQuest must run an entire simulation before determining whether the results are requirement-infeasible.
To avoid running requirement-infeasible simulations, OptQuest must identify the characteristics of solutions likely to be requirement-feasible. This makes the search more complex and requires more time.
When you use requirements, you should increase the search time by at least 50% (based on the time used for an equivalent problem without requirements).