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Research on airport multi-objective optimization of stand allocation based on simulated annealing algorithm.

Ningning Zhao1, Mingming Duan1

  • 1College of Air Traffic Management, CAUC, Tianjin 300300, China.

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|November 24, 2021
PubMed
Summary

This study optimizes airport gate allocation using a mathematical model, significantly reducing passenger travel, airline costs, and improving gate usage efficiency. The new model offers substantial improvements over current airport practices.

Keywords:
Standairline costmulti-objective optimizationpre-allocationsimulated annealing

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Area of Science:

  • Operations Research
  • Transportation Science
  • Airport Management

Background:

  • Efficient airport gate allocation is crucial for operational efficiency and passenger satisfaction.
  • Current pre-allocation strategies may not optimize multiple objectives simultaneously.
  • Lanzhou Zhongchuan Airport serves as a case study for evaluating allocation models.

Purpose of the Study:

  • To develop a multi-objective optimized mathematical model for airport stand pre-allocation.
  • To minimize passenger travel distance, airline costs, and maximize gate usage efficiency.
  • To assess the practical applicability and benefits of the proposed model.

Main Methods:

  • Construction of a multi-objective optimized mathematical model for stand pre-allocation.
  • Application of the model using actual flight data from 12 flights at Lanzhou Zhongchuan Airport.
  • Solving the optimization problem using the simulated annealing algorithm.

Main Results:

  • The optimized allocation scheme reduced the total objective function by 40.67% compared to the airport's actual scheme.
  • Passenger travel distance was reduced by 4512 steps.
  • Gate usage efficiency increased by 31%, one gate was saved, and airline costs decreased by 300 RMB.

Conclusions:

  • The developed mathematical model demonstrates significant practical value for airport stand pre-allocation.
  • The model effectively balances objectives of passenger convenience, airline cost, and resource utilization.
  • Implementation of this model can lead to substantial operational improvements in airport management.