Robustness analysis of binary-coupled logistics–supply chain interdependent networks under load redistribution

To capture the interdependencies between logistics and supply chain networks in real-world systems, this paper develops a load redistribution-based logistics–supply chain binary-coupled network (LSBCN) model. Employing a dynamic load redistribution strategy, we systematically investigate the robustness of the LSBCN under cascading failures. We evaluate network performance under both random and deliberate failures, thoroughly analyze the mechanisms of influence of capacity factor (β) and capacity index (γ) on network robustness, and design three optimization strategies: parameter optimization, critical edge protection, and redundant edge addition. Furthermore, we quantitatively examine the synergistic effects and cost-effectiveness among these strategies. The results reveal that capacity factors exert significant regulatory effects on network robustness; however, the marginal improvement diminishes beyond a critical threshold. Distinct optimal capacity parameter configurations correspond to different failure proportions. Protecting critical edges of the logistics network demonstrates superior robustness enhancement under random failures, whereas adding redundant edges proves more effective under deliberate failures. The synergistic effects between strategies exhibit strong dependence on both failure modes and proportions. Under random failures, critical edge protection should be prioritized, while under deliberate failures, redundant edge addition is preferable. These findings provide theoretical foundations and decision-making references for vulnerability assessment, collaborative optimization, and risk management in logistics–supply chain systems.