To ensure viability, it is necessary for an intertwined supply network (ISN) system to optimise network structure to provide flexible redundancy in response to changing environment. Considering resilience methods are usually designed as reactions to single discrete disruptions rather than situational reactions to real-time changes, this study proposes a novel redundancy optimisation approach dynamically providing each demand market with a pair of supply routes to optimise the flexible redundancy of ISN, thereby ensuring the survivability of supply chains and demand markets under continuous changes. Based on this, we propose the ISN design (ISND) model to capture the trade-off between total cost and viability performance under facility and transportation disruption. The Lagrangian relaxation algorithm, combined with the sub-gradient method and the improved cellular genetic algorithm, are utilised for solving problems of different scales. To test the performance of the model and corresponding algorithms, we also conduct a numerical analysis of the data from medical equipment ISN in southern China. The results indicate that the ISND model can effectively optimise ISN structures, which makes it possible to dynamically provide flexible redundancy; the two algorithms also show good calculation efficiency. The relationship between ISN structure and viability performance is thus observed and explained.