Joint optimisation of product family configuration and supply chain resilience

A product family consists of multiple components, often supplied by various suppliers. It is crucial to consider the supply risk of these suppliers during product family configuration to ensure that orders can be replenished by alternative suppliers in the event of component disruptions. This study establishes a new optimisation model that concurrently addresses product family configuration and supply chain resilience for the first time. The model is further linearised, making it readily solvable using commercial optimisation software packages for smaller-scale problems. A nested genetic algorithm for solving the large-scale problems is also developed. The proposed method is demonstrated through a case study involving e-book products. The numerical results indicate that the joint optimisation method outperforms other methods, and the nested genetic algorithm achieves high-quality near-optimal solutions with good stability. A sensitivity analysis based on the e-book case assesses the impact of several parameters on profit, including supplier flexibility, unit loss cost, and disruption probability. The findings underscore the importance of supplier flexibility in supplier selection and suggest that companies should carefully evaluate unit loss costs across different module instances, as well as the regional risks associated with suppliers.