The problem we consider is to determine a set of parts and processes that realizes the design in a Pareto optimal manner with respect to cost and quality. Note that nj represents a redundancy element that is usually considered while designing electronic devices, We assume that all the above quantities are provided as input data. However, the problem has been relatively well studied and a number of solution strategies have been reported in the operations research literature. A tricky issue in our application here is that we would like to generate a set of Pareto optimal solutions parameterized with respect to l. Hence, in selecting a solution procedure, besides efficiency and accuracy we also need to consider the ease with which parametric analysis could be carried out.
P becomes easy to solve.
In fact, it is easy to show that the following greedy assignment rule produces an optimal solution. P' of selected processes, the greedy algorithm stated above first assigns the cheapest process for each part alternative. It then costs out each part alternative and subsequently selects the minimum cost alternative for each generic part type. It can easily be shown that the above algorithm generates an optimal solution. The greedy approach however does not permit a straightforward procedure for parametric analysis with respect to l.