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An integrated optimization mode for multi-type aircraft flight scheduling and routing problem.

Ming Wei1, Li Gang Zhao2,3, Zhi Jian Ye1

  • 1School of Air traffic Management, Civil Aviation University of China, Tianjin 300300, China.

Mathematical Biosciences and Engineering : MBE
|October 30, 2020
PubMed
Summary

This study introduces an optimization model for integrated aircraft flight scheduling and routing. It minimizes costs and maximizes passengers by optimizing flight times and aircraft assignments, validated by a Chinese airline case study.

Keywords:
aircraft routingflight schedulingheuristic algorithmmulti-objectivemultiple-aircraft type

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Area of Science:

  • Operations Research
  • Aviation Management
  • Transportation Science

Background:

  • The integrated aircraft flight scheduling and routing problem is complex, requiring simultaneous optimization of flight times and aircraft assignments.
  • Existing models often fail to account for flexible flight windows, aircraft availability, and simultaneous cost minimization and passenger maximization.

Purpose of the Study:

  • To develop an optimization model for the integrated aircraft flight scheduling and routing problem.
  • To minimize operational costs (aircraft number, idle time) and maximize transported passengers.
  • To present an efficient heuristic approach for finding optimal solutions.

Main Methods:

  • A novel optimization model is proposed, considering flexible departure/arrival times and aircraft distribution.
  • A two-stage heuristic approach using Ant Colony Optimization (ACO) and a polynomial algorithm is developed.
  • The model accounts for aircraft type, flexible time windows, and initial aircraft distribution.

Main Results:

  • The model effectively minimizes weighted operation costs and maximizes passenger numbers.
  • The Ant Colony Optimization-based heuristic efficiently generates acceptable solutions for aircraft routes and timetables.
  • A case study with a Chinese airline demonstrates the model's feasibility and superiority over conventional methods.

Conclusions:

  • The proposed integrated model offers a robust solution for optimizing aircraft flight scheduling and routing.
  • The heuristic approach provides an efficient method for solving complex airline operational problems.
  • The model's successful application in a real-world case study validates its practical utility and effectiveness.