Exact reliability of cold chain networks with multi-state travel time and transport capacity

Post-pandemic lifestyle changes have increased reliance on e-commerce, boosting the logistics sector. One of the most highly regarded industries is cold chain logistics, especially for vaccines and refrigerated foods. In cold chain networks, transport routes have varying capacities based on customer orders, and travel times fluctuate due to traffic and weather. Thus, this study focuses on evaluating network reliability, i.e., the probability to meet given demands within the specified time threshold, of cold chain networks considering the two multi-state factors: travel time and transport capacity. To account for practical situations, a multi-state cold chain network (MCCN) is constructed with retailers, third-party logistics companies, and suppliers as nodes, and transportation routes as arcs. The concept of minimal path is used to determine the transport flow that complies with the time threshold and to determine the transport capacity vectors that satisfy the demands. An algorithm is proposed to resolve different characteristics of time thresholds and demand requirements for efficient assessment. Network reliability is successfully calculated, as shown in the case and sensitivity analysis. This allows managers to grasp the performance of MCCN and make informed decisions based on the achieved network reliability.