Optimization Variables and the Design Space

Once the optimization variables are specified, the optimizer handles each of them as an n-dimensional vector x. Any point in the design space corresponds to a particular x-vector and to a design instance. Each design instance may be evaluated via FEA and assigned a cost value; therefore, the cost function is defined over the design space (cost(x): Rⁿ→ R, where n is the number of optimization variables.

In practice, a solution of the minimization problem is sought only on a bounded subset of the Rn space. This subset is called the feasible domain and is defined via linear constraints.