Optimization studies are used to find the parameter values of a model that minimizes or maximizes a particular objective function subject to a number of constraints.  A special form of optimization problem, called System Identification, can also be solved in an optimization study.  In this case, the objective function is to minimize the quadratic deviation of a given function from a target function.

To formulate a design problem as an optimization problem, input variables, objective and constraint functions need to be defined.  There can be single or multiple objective functions.  Optimization can be applied to any one or more analysis codes and hence can be multi-disciplinary.  Size and shape optimizations can be performed.  Problems can be either deterministic or probabilistic, where the objective is to meet a certain reliability and robustness target.

Optimization can be performed using the analysis solver directly, or by using a fitting function (approximation, response surface).

The steps to set up a Optimization approach in HyperStudy are: