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Airline Fleet Assignment Problems with Binary and Integer Programming models: Classical vs Quantum Annealing

Kuntal Adak, Sakshi Kaushik, Rahul Rana

Abstract

This research highlights the potential of quantum annealing in tackling large-scale optimization problems within the airline industry,demonstrating its efficiency for certain problem sizes while also acknowledging its current limitations. The comparative analysis provides valuable insights into the performance of advanced computational techniques, paving the way for further advancements in optimizing fleet assignments in the aviation sector.

Airline Fleet Assignment Problems with Binary and Integer Programming models: Classical vs Quantum Annealing

Abstract

This research highlights the potential of quantum annealing in tackling large-scale optimization problems within the airline industry,demonstrating its efficiency for certain problem sizes while also acknowledging its current limitations. The comparative analysis provides valuable insights into the performance of advanced computational techniques, paving the way for further advancements in optimizing fleet assignments in the aviation sector.
Paper Structure (17 sections, 3 equations, 9 figures, 10 tables)

This paper contains 17 sections, 3 equations, 9 figures, 10 tables.

Table of Contents

  1. Introduction
  2. Literature Survey
  3. Problem Formulation
  4. BLP Model for Multi-Day Fleet Type Assignment:
  5. ILP model for Single-Day Fleet Type Assignment
  6. Methodology
  7. Data
  8. Solution Approach
  9. Solver
  10. SCIP
  11. Quantum Annealing
  12. Results
  13. BLP Model for Multi-Day Fleet Type Assignment:
  14. ILP Model for Single-Day Fleet Type Assignment:
  15. Conclusion
  16. ...and 2 more sections

Figures (9)

  • Figure 1: Flight scheduling Process overview
  • Figure 2: Architecture of Quantum Hybrid Solvers bib19
  • Figure 3: Flight to Fleet assignment (BLP) Time-line network (for the day1 results getting from SCIP and LHCQM) depicting the flights departing and arriving at a particular location. Each fleet type is depicted with a different color. Flights are assigned based on the objective of minimizing the cost, considering the difference between capacity and demand of passengers while meeting a set of operational and logistical constraints. The incoming arrow shows the flights arriving at a location and the outgoing arrows show the flights departing from that location
  • Figure 4: Comparison of optimal cost (AUD) for both solvers in Fleet assignment (BLP) model
  • Figure 5: Comparison of solution time (sec) for both solvers in Fleet assignment (BLP) model
  • ...and 4 more figures