  Assume that a set of $P$ process parameters $p_i$, $i=1,\dots,P$, determines
the outcome of a set of $D$ descriptor variables $d_j$, $j=1,\dots,D$, via an
unknown functional relationship $\phi: \mathbf{p} \mapsto \mathbf{d}, \,
\mathbb{R}^{P} \to \mathbb{R}^{D}$, where $\mathbf{p}=(p_1,\dots,p_{P})$,
$\mathbf{d}=(d_1,\dots,d_{D})$. It is desired to find appropriate values
$\mathbf{\hat p} = ({\hat p}_1,\dots, {\hat p}_P)$ for the process parameters
such that the corresponding values of the descriptor variables $\phi (\mathbf
{\hat p})$ are close to a given target $\mathbf d^*=(d^*_1,\dots,d^*_D)$,
assuming that at least one exact solution exists. A sequential approach using
dimension reduction techniques has been developed to achieve this. In a
simulation study, results of the suggested approach and the algorithms NSGA-II,
SMS-EMOA and MOEA/D are compared.
