A two-stage decision-support approach for improving sustainable last-mile cold chain logistics operations of COVID-19 vaccines
针对新冠疫苗最后一英里冷链物流面临的低温运输、供应不确定等挑战，提出一种集成路线优化与仿真的两阶段决策支持方法，并通过挪威实际案例分析了网络结构、车队规模等对服务水平、成本和碳排放的影响。
Abstract The COVID-19 pandemic has become a global health and humanitarian crisis that catastrophically affects many industries. To control the disease spread and restore normal lives, mass vaccination is considered the most effective way. However, the sustainable last-mile cold chain logistics operations of COVID-19 vaccines is a complex short-term planning problem that faces many practical challenges, e.g., low-temperature storage and transportation, supply uncertainty at the early stage, etc. To tackle these challenges, a two-stage decision-support approach is proposed in this paper, which integrates both route optimization and advanced simulation to improve the sustainable performance of last-mile vaccine cold chain logistics operations. Through a real-world case study in Norway during December 2020 and March 2021, the analytical results revealed that the logistics network structure, fleet size, and the composition of heterogeneous vehicles might yield significant impacts on the service level, transportation cost, and CO 2 emissions of last-mile vaccine cold chain logistics operations.