| Summary: | Facing rapid growth in air cargo demand within the global supply chain and limitations of traditional storage location allocation methods, this study proposes an intelligent optimization strategy for storage location allocation. The strategy considers key factors like flight schedules, cargo collection and delivery data, cargo terminal topology, and in-and-out paths. It intelligently allocates each cargo batch to the most suitable location, assigning more flights' cargo to locations near the exit, thereby reducing cargo handling distance and offloading time, and enhancing operational efficiency and cargo handling capacity in the air freight sector. The algorithm, based on the latest optimization theories and techniques, seeks optimal solutions under various constraints. The model and algorithm’s effectiveness is validated through simulation experiments using actual flight data. The results indicate that, compared to traditional strategies, the optimized strategy reduces response time by 62%.
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