SCHEDULING AIRCRAFT LANDING

# SCHEDULING AIRCRAFT LANDING

## SCHEDULING AIRCRAFT LANDING

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
##### Presentation Transcript

1. SCHEDULINGAIRCRAFT LANDING Mike Gerson Albina Shapiro

2. Background • Air traffic has been on the rise for decades, but there has not been a corresponding increase in the number of airports and runways • Airlines are forced to improve their efficiency • High capital investments and operational costs • Heightened security • Increased competition due to low-cost airlines • Little tactical planning is currently done – sequence is approximately FCFS • Planning allows delays to be assigned before departure: delays on the ground are half as costly as in the air • Allows for different objectives to be met (besides just getting all the planes on the ground)

3. Potential Objectives • Punctuality • Minimize average lateness or number of late planes • Efficiency • Maximize airport capacity (similar to minimizing makespan) • Costs • Minimize costs

4. The Decision Problem An airport's Air Traffic Control (ATC) is responsible for creating a schedule of plane landings • Separation Times • Mandatory inter-landing time between planes (wake vortex), determined by plane size and visibility • Time window • Bounded by earliest time a plane can land (flying at maximum speed) and by latest a plane can land (flying at most fuel-efficient speed while circling for maximum possible time) • Plane’s cruise speed • A plane’s most economical speed. A cost is incurred if the plane is forced to deviate from this speed.

5. Job Shop Model Early research (late 1970s) modeled problem as a job shop Runways = machines Planes = jobs Earliest feasible landing time = release date • Sequence-dependent processing times • Maintains separation time • Typical objective function: minimize makespan • And the problem becomes np-hard!

6. Prioritizing Flights Allows airlines to set their own preferences • Size of plane or number of passengers • Connecting flights (passengers and cargo) • Fuel capacity considerations • 1998 – Carr, et al • Priority ranking system per airline • Objective: minimize deviations from preferred order

7. Prioritizing Flights • 1995 – Abela, et al, 2000 – Beasley, et al • Simple cost function, linearly tied to deviation from a target arrival time • Objective: Minimize weighted deviations from scheduled time

8. Prioritizing Flights • 2008 – Soomer and Franx • More complex linear cost function more accurately accounts for airline preferences • Includes scaling procedure to normalize costs between airlines (prevents one airline from receiving priority for a higher cost structure) • Objective:Minimize total scaled cost

9. Solution Methods • Simulation • Genetic algorithms • Population heuristics • Formulate mixed-integer programming model • Branch and bound • Use an upper bound heuristic, then LP-based tree search • Local search heuristic

10. Local Search Heuristic Swap neighborhood Shift neighborhood

11. Results • Soomer, et al: Local Search Heuristic • Significant cost savings over FCFS • Average savings per flight: 33% of FCFS costs • Total savings: 81% of scaled costs

12. Advantages over FCFS • Cost Savings • Consistent Performance • Automated system vs human judgment • Allows active scheduling • Computations run quickly enough to allow updated schedules to be calculated as circumstances change (departure delays, weather conditions, etc)

13. References • J. Abela, D. Abramson, M. Krishnamoorthy, A. De Silva, and G. Mills, “Computing Optimal Schedules for Landing Aircraft,” in Proceedings of the 12th National ASOR Conference, Adelaide, Australia, (1993) 71-90. • G.C. Carr, H. Erzberger, F. Neuman. “Airline Arrival Prioritization in Sequencing and Scheduling,” in Proceedings of the 2nd USA/EUROPE Air Traffic Management R&D Seminar (1998). • J.E. Beasley, M. Krishnamoorthy, Y.M. Sharaiha, D. Abramson, “Scheduling Aircraft Landings – The Static Case,” in Transportation Science 34 (2000) 180–197. • J.E. Beasley, J. Sonander, P. Havelock, “Scheduling Aircraft Landings at London Heathrow using a Population Heuristic,” in Journal of the Operational Research Society 52 (2001) 483–493. • M.J. Soomer, G.J. Franx, “Scheduling Aircraft Landings using Airlines’ Preferences,” in European Journal of Operational Research 190 (2008) 277-291.