Abstract
To offer a wide product variety to customers in a cost-efficient way, companies have introduced platforms, defined as a base from which different products can be derived. We consider a product portfolio, consisting of a set of end products, where each product has a set of attributes (features), which can have different levels requested by the customers. We present a model to support companies in designing the cost-minimizing platform portfolio, consisting of a set of platforms, from which these products can be derived. Each platform has a set of technical design parameters, which can have different levels. The required parameter levels in the platform’s design depend on the attribute needs of the products derived from the platform. Our model gives guidance to what extent the platforms should be under-designed, over-designed or the same with regard to the products (and its attribute levels) derived from them. The model quantifies the impact of these platform portfolio decisions on the relevant operational costs. Given the complexity of this problem for large-scale instances, we develop two fathoming rules to improve computational efficiency. These fathoming rules can be used in different solution algorithms. We illustrate their applicability in a branch-and-bound, simulated annealing and genetic algorithm. We demonstrate the value of our model and solution method with a practical case of a high-tech screen manufacturing company, that wants to design the cost-minimizing platform portfolio from which their product portfolio can be derived.
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