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Facing a fiercely turbulent and uncertain market competition environment, enterprises in the cluster supply chain (CSC) network system must rapidly respond to fluctuating customer demands while ensuring high customer service. In addition to cross-chain order collaboration, they are required to maintain a certain amount of safety stock due to their limited capacity. However, research gaps exist in configuring collaborative manufacturing CSC networks that integrate order collaboration, safety stock placement, and mode selection. This study addresses the optimal configuration of such a CSC system under capacity constraints and a guaranteed service model. A distributed decision-making optimisation model is developed, simultaneously considering mode selection, inventory positioning, order subcontracting, and privacy protection. Augmented Lagrangian coordination (ALC) is used to coordinate sub-models, solved via a proposed heuristic-based genetic algorithm. Numerical experiments analyse the impacts of capacity constraints and demand fluctuations on the optimal configuration of the CSC network system. Key findings include: balancing time and cost by allocating cooperative order ratios enhances customer service and CSC system competitiveness during high demand fluctuations; the reduced capacity of selected CSC participants can be managed by adjusting safety stock levels or shortening external service times to address dynamic changes.
Nie et al. (Wed,) studied this question.