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A Quantitative Fitness Analysis Workflow
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A Fuzzy Crew Rostering Model Based on Crew Preferences and Seniorities considering Training Courses: A Robust

Bahareh Shafipour-Omrani1, Alireza Rashidi Komijan2, Seyed Jafar Sadjadi3

  • 1Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran.

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Summary
This summary is machine-generated.

This study introduces an innovative crew rostering model to optimize crew assignments by maximizing preferences and minimizing undesirable schedules. The genetic algorithm approach significantly reduces suboptimal rosters, improving airline operations.

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Area of Science:

  • Operations Research
  • Aviation Management
  • Computer Science

Background:

  • The crew scheduling problem is a critical aspect of airline operations, divided into crew pairing and crew rostering.
  • Existing models often struggle to balance crew preferences, operational constraints, and uncertainties.

Purpose of the Study:

  • To develop an advanced crew rostering model that maximizes crew satisfaction and adheres to regulations.
  • To address the challenge of inconsistent crew assignments and uncertainty in seniority weights and time away from base.

Main Methods:

  • Formulation of a rostering model incorporating crew preferences, seniority, regulations, and training attendance.
  • Introduction of a novel scoring mechanism for desirable and undesirable assignments.
  • Application of fuzzy logic for seniority weights and development of a robust counterpart for time away from base uncertainty.
  • Utilization of a genetic algorithm (GA) for solving the crew rostering problem (CRP).

Main Results:

  • The proposed model effectively assigns crew to pairings, maximizing weighted preferences and minimizing penalties.
  • The genetic algorithm achieved an average optimality gap of only 0.5%, demonstrating high efficiency.
  • Real-world data from Air India Airline showed a 61.59% reduction in undesirable rosters compared to previous methods.

Conclusions:

  • The developed crew rostering model offers a significant improvement in crew satisfaction and operational efficiency.
  • The novel scoring mechanism and handling of uncertainties provide a more robust and effective solution for airline crew scheduling.
  • This research presents a pioneering approach to inconsistent crew rostering and demonstrates substantial reductions in undesirable outcomes.