| Citation: | ZHANG J，ZHANG Z R，HONG Z C，et al. Robust optimization of aviation logistics network in context of COVID-19 pandamic[J]. Journal of Beijing University of Aeronautics and Astronautics，2023，49（9）：2218-2226 （in Chinese） doi: 10.13700/j.bh.1001-5965.2021.0664
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To deal with the risk of reducing the capacity of passenger aircraft bellies due to the interruption of passenger aircraft routes in the context of COVID-19 pandemic, and to improve the robustness of the aviation logistics network at a minimum cost, a study on the allocation and route optimization of all-cargo aircraft routes under the situation of uncertain passenger aircraft belly storage capacity was proposed. With the objective of minimizing the total cost of the route network while considering transportation mode, air cargo demand, and transportation distance between cities, this study established a robust optimization model for the aviation logistics network under the uncertain passenger aircraft bellies. The column-and-constraint generation (C&CG) algorithm was effectively used to solve the model. In addition, this paper investigated the optimized layout of aviation logistics network routes using the case study and data of company S. The results show that the two-stage robust optimization method for aviation logistics network can effectively reduce cost changes caused by reduced passenger aircraft belly capacity, and the robust solution can reduce the cost of the aviation logistics network by 20.7% in the extreme case of complete disruption of passenger routes. Therefore, this study concluded that the use of the two-stage robust optimization method enables decision-makers to flexibly select cargo aircraft routing while considering the economy and robustness of the aviation logistics network under the influence of uncertainty surrounding passenger aircraft belly capacity.
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