Airline capacity distribution under financial budget and resource consideration

Area of Science:

• Operations Research
• Aviation Management
• Optimization

Background:

• Airline capacity distribution is a complex optimization problem.
• It involves long-term planning and short-term operational decisions.
• Financial budget and resource constraints add significant challenges.

Purpose of the Study:

• To investigate the airline capacity distribution problem considering financial and resource limitations.
• To develop an effective algorithm for solving this large-scale optimization problem.
• To improve decision-making in financial budget arrangement, fleet introduction, and fleet assignment.

Main Methods:

• Formulation of an integer programming model.
• Development of an integrated algorithm combining modified Variable Neighborhood Search (VNS) and Branch-and-bound (B&B).
• Utilization of a greedy heuristic for initial fleet introduction solutions and B&B for optimal fleet assignment.

Main Results:

• The hybrid algorithm demonstrates powerful performance in objective value, convergence speed, and stability.
• Budget limit checks were successfully integrated into financial budget arrangements.
• Comparative analysis showed superior results compared to basic VNS, differential evolution, and genetic algorithms.

Conclusions:

• The developed hybrid algorithm is an effective approach for airline capacity distribution.
• The method provides a robust solution for optimizing airline operations under budget and resource constraints.
• The findings contribute to more efficient and stable airline management strategies.