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Research on the scheduling method of ground resource under uncertain arrival time

Author

Listed:
  • Xu, Guoning
  • Lin, Yupeng
  • Wu, Zhiying
  • Chen, Qingxin
  • Mao, Ning

Abstract

We present a two-stage scheduling approach including proactive and reactive scheduling to solve the ground resource scheduling problem with uncertain arrival time. In the first stage, an integer programming model is constructed to minimize the delay and transfer costs. After solving this model, we obtain a baseline scheduling plan that considers the service arrival time uncertainty. In the second stage, the feasibility of the subsequent benchmark plan is evaluated based on the current state of the services and resources. The reactive scheduling model is enabled when trigger conditions are met. Moreover, an improved adaptive large neighborhood search is designed to solve the proactive scheduling model effectively. Real data from an international airport in South China is used as a test case to compare different scheduling strategies. The results show that it is difficult to handle the uncertainty of the problem with the benchmark plan that simply considered buffer time. Compared with rolling time-domain scheduling, the average transfer cost of the scheduling strategy proposed in this paper increased slightly, but the average service delay cost can be reduced significantly. Algorithm-wise, instances of different scales are designed to verify the effectiveness of the improved adaptive large neighborhood search algorithm. The efficiency of the algorithm scheme is better than that of the Gurobi solver scheme in medium to large-scale problems. Therefore, the forward and reactive strategies can better handle the uncertainty of airport ground protection services as they can simultaneously guide the allocation and utilization of airport ground protection resources.

Suggested Citation

  • Xu, Guoning & Lin, Yupeng & Wu, Zhiying & Chen, Qingxin & Mao, Ning, 2023. "Research on the scheduling method of ground resource under uncertain arrival time," Operations Research Perspectives, Elsevier, vol. 11(C).
  • Handle: RePEc:eee:oprepe:v:11:y:2023:i:c:s221471602300026x
    DOI: 10.1016/j.orp.2023.100291
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