基于旅客重新分配的机场安检队列有效管理
Effective Management of Airport Security Queues with Passenger Reassignment
AI总结：
本文针对机场安检高峰拥堵问题，将旅客重新分配到σ分钟时段的调度任务建模为最小费用网络流问题，实现多项式时间精确求解，并通过初步实验验证其在提升吞吐量、减少等待时间和改善旅客满意度方面的有效性。
摘要：
机场安检队列常常效率低下，导致等待时间过长和吞吐量下降，尤其是在出发高峰时段，影响旅客和航空公司。本文研究将旅客重新分配到特定安检时段的问题，旨在缓解这些低效现象。我们将该问题建模为最小费用网络流（Minimum Cost Network Flow，MCNF）问题，由于其线性规划结构，能够在多项式时间内精确求解。我们的方法在不同时间区间之间重新分配旅客需求。通过优化将旅客重新分配到以σ分钟为单位的时段，我们在吞吐量和等待时间方面取得了显著改善。初步结果证明了该方法在提升运营效率和旅客满意度方面的有效性。MCNF 公式提供了一种可扩展且适应性强的解决方案，为机场安检管理带来长期效益。
英文摘要：
Airport security queues often suffer from inefficiencies that result in long wait times and decreased throughput, especially at peak departure time, affecting both passengers and airlines. This work addresses the problem of reassigning passengers to specific time slots for crossing security, aiming to mitigate these inefficiencies. We frame this problem as a Minimum Cost Network Flow (MCNF) problem, enabling us to solve it exactly in polynomial time due to its linear programming structure. Our approach redistributes passenger demand across different time intervals. By optimizing the reassignment of passengers to sigma-minute time slots, we achieve significant improvements in throughput and reductions in waiting time. Preliminary results demonstrate the effectiveness of our method in enhancing operational efficiency and passenger satisfaction. The MCNF formulation offers a scalable and adaptable solution, providing long-term benefits for airport security management.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
