Resilience measurement and dynamic optimization of container logistics supply chain under adverse events

Adverse events may cause chaotic phenomena such as uncertain delay, port congestion, and slow turnover efficiency of container ships, making the container logistics supply chain (CLSC) suffer a serious impact. In order to fully describe and model the adverse events, and further adjust and optimize the container logistics system, this study designs a two-stage container logistics supply chain model, mainly including a container pretreatment system (CPS) and a container handling system (CHS). Taking into account the real-time measurement of the overall CLSC resilience and the need to guide the adjustment method, a novel two-dimensional resilience index in terms of affordability and recovery ability is proposed to reveal the inherent resilience performance of the system. By decomposing the resilience index, the interaction mechanism between the internal elements can be further explored. An adaptive fuzzy double-feedback adjustment (AFDA) control structure is designed to optimize the two-stage CLSC system in order to alleviate the influence of adverse events, enhance the response and resilience performance, and stabilize the system as soon as possible. The simulation results show that under the influence of adverse events, the resilience performance and the ability to maintain stability is obviously weakened. Through feedback control of two-stage system responses, the above adverse effects can be effectively alleviated. Compared with other existing optimization strategies, the dynamic optimization method designed in is paper is more conducive to improving the response performance and enhancing the resilience of the system. The rationality and effectiveness are also verified by the simulation results.