Passengers rescheduling to minimise check-in time and conveyor belt degradation
研究了一种乘客重新调度方法，通过两阶段优化同时减少值机总时间和传送带磨损，实验显示优于传统FIFO和贪婪算法。
With the resurgence of air travel post-COVID-19, airports face increasing challenges in managing check-in operations efficiently while ensuring the longevity of critical equipment. This study presents a novel approach to passenger rescheduling that minimises total check-in time and reduces conveyor belt degradation. The problem is formulated as a Parallel Machine Rescheduling Problem (PMRP), addressed through a two-phase solution. In the first phase, a Mixed-Integer Linear Programming (MILP) model optimally assigns passengers to check-in counters, focusing on initial efficiency. In the second phase, dynamic optimisation heuristic reallocates passengers as they arrive, minimising wait times and balancing the load on conveyors based on baggage weights. Experimental results demonstrate that the proposed method achieves significant improvements in both operational efficiency and conveyor belt durability, outperforming traditional FIFO and Greedy Algorithm. By integrating maintenance considerations into passenger scheduling and introducing a robust predictive-reactive strategy, this research provides practical tools for airports to enhance operational resilience and infrastructure sustainability.