Disturbance-Aware Multi-Criteria Network Optimization for Carrier Selection and Risk-Aware Routing in Multimodal Logistics Systems

Background: Efficient carrier selection and routing in multimodal logistics networks is increasingly complex due to operational uncertainty, fluctuating service reliability, and the need for disturbance-aware decision-support tools. This study develops an integrated optimization framework for simultaneous carrier selection and routing under operational disturbances. Methods: A disturbance-aware multi-criteria network optimization model is proposed that incorporates transportation cost, delivery time, reliability, and economic risk within a unified mathematical formulation. Operational disturbances are represented as parametric perturbations of network costs, enabling recalculation of routing decisions. Computational experiments were conducted on an illustrative multimodal network and additional synthetic networks. Results: The results show that routing decisions remain stable under disturbance levels up to 5% and reconfigure under higher perturbations. Comparative analysis with a classical cost-minimization routing model illustrates a potential reduction in expected economic risk exposure of approximately 25–30% within the illustrative experimental setting while maintaining comparable transportation time. Conclusions: The proposed framework integrates carrier selection and routing decisions in multimodal logistics systems and supports risk-aware decision-making under operational uncertainty.