Simultaneous configuration of product families and supply chains for mass customization using leader-follower game theory

With the manufacturer with mass customization paradigm extending its scope into global manufacturing network, module-based product family configuration and supply chain design should be simultaneously considered. This paper formulates joint optimization of product family and supply chain configuration as a leader-flower Stackelberg game. Product family configuration is modeled as a upper level problem (leader) with the selections of product variants, modules and module instances as decision factors, while the supply chain, as a lower level problem (follower), determines the configuration of supply chain networks in terms of the decisions from the upper level. A nonlinear, mixed integer programming model is built for the bi-level joint optimization. The genetic algorithm is developed to solve the leader-follower bi-level game. A case study of a power transformer product family is reported to demonstrate the effectiveness of the proposed method.