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A Rapid Method for Modeling a Variable Cycle Engine
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Dynamic multi-objective aviation maintenance scheduling: an algorithmic framework.

Le Qi1,2, Chen Lv1, Tao Zhang3

  • 1School of Reliability and Systems Engineering, Beihang University, Beihang, China.

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|February 17, 2026
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Summary
This summary is machine-generated.

This study presents a new framework for aviation maintenance scheduling, optimizing real-time operations. The proposed methods significantly reduce costs and improve efficiency in complex scheduling environments.

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Area of Science:

  • Operations Research
  • Aerospace Engineering
  • Computational Optimization

Background:

  • Aviation maintenance scheduling is complex, facing dynamic task arrivals and variable service times.
  • Balancing competing objectives like cost and efficiency is a key challenge.

Purpose of the Study:

  • To develop a novel real-time, multi-objective optimization framework for aviation maintenance scheduling.
  • To integrate dynamic task arrivals, stochastic service times, and competing objectives into a unified model.

Main Methods:

  • Developed a framework combining mathematical modeling with meta-heuristic algorithms.
  • Evaluated nine algorithms across 810 experimental configurations.
  • Provided new theoretical performance guarantees for the proposed methods.

Main Results:

  • Proposed methods achieved statistically significant improvements over baseline scheduling.
  • Adaptive Tabu Search (ATS) yielded the lowest single-objective cost ($13,072 ± $4544).
  • Multi-objective methods generated diverse Pareto fronts with a mean hypervolume of 0.0268, dominating more objective space.

Conclusions:

  • The framework offers significant potential for operational cost reductions in aviation maintenance.
  • Provides a robust theoretical foundation for next-generation maintenance scheduling systems.
  • Demonstrates superior performance compared to existing scheduling approaches.