Slavomir Bednar, Vladimir Modrak
The development of methods to identify the optimal product variety of a product platform is an important research issue in mass customization. A product platform which includes a wide portfolio of modules or components allows customers to customize their product by expressing a lot of different requirements. However, certain requirements may be constrained each other thus bringing customers to be disappointed by unfeasible product configurations. The present article explores the possibility of using entropy-based measures for quantifying the complexity induced by product variety in the context of constrained product configuration. More specifically, this article proposes a method which uses entropy-based measures to decide the optimal variety for product platforms. This method characterises a given product platform comparing the entropy associated to the feasible product configurations with the entropy associated to the unfeasible product configurations. Computational experiments performed on two case applications show that the proposed method can be effectively used to quantify variety-induced complexity and to assist product managers to choose optimal product variety.