Summary
The airline network is one of the world’s most sophisticated, yet very complex, networks. Airline planning and scheduling operations have posed many great logistics challenges to operations researchers. Optimizing flight schedules, maximizing aircraft utilization, and minimizing aircraft maintenance costs can drastically improve the airlines’ resource management, competitive position and profitability. However, optimizing today’s airline complex networks is not an easy task. There are four major optimization problems in the airline industry including flight scheduling problem, fleet assignment problem, crew pairing problem, and aircraft maintenance routing problem. These problems have been widely studied over the past few decades. Yet, they remain unsolved due to the size and complexity. In this chapter, we provide a review of advances in optimization applied to these logistics problems in the airline industry as well as give a thorough discussion on the aircraft maintenance routing problem. Several mathematical formulations and solution methods for the aircraft maintenance routing problem will also be presented. Later, we conclude the current research and discuss possible future research of this problem.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
Refereneces
C. Barnhart, N. Boland, L. Clarke, E. Johnson, G. Nemhauser, and R. Shenoi. Flight string models for aircraft fleeting and routing. Transportation Science, 32(3):208–220, 1998.
C. Barnhart, E. Johnson, G. Nemhauser, and P. Vance. Crew scheduling. In R.W. Hall, editor, Handbook of Transportation Science, pages 493–521. Kluwer Scientific Publishers, 1999.
N. Boland, L. Clarke, and G. Nemhauser. The asymmetric traveling salesman problem with replenishment arcs. European Journal of Operational Research, 123:408–427, 2000.
G. Chartrand and O. Oellermann. Applied and Algorithmic Graph Theory. McGraw-Hill, 1993.
L. Clarke, C. A. Hane, E. Johnson, and G. Nemhauser. Maintenance and crew considerations in the fleet assignment. Transportation Science, 30(3):249–260, 1996.
L. Clarke, E. Johnson, G. Nemhauser, and Z. Zhu. The aircraft rotation problem. Annals of Operations Research, 69:33–46, 1997.
A. Cohn and C. Barnhart. Improving crew scheduling by incorporating key maintenance routing decisions. Operations Research, 51(3):387–396, 2003.
J. Cordeau, G. Stojkoviac, F. Soumis, and J. Desrosiers. Benders decomposition for simultaneous aircraft routing and crew scheduling. Transportation Science, 35(4):375–388, 2001.
M. Elf and V. Kaibel. Rotation planning for the continental service of a European airline. In W. Jager and H. Krebs, editors, Mathematics - Key Technologies for the Future: Joint Projects between Universities and Industry, pages 675–689. Springer, 2003.
A. Erdmann, A. Nolte, A. Noltemeier, and R. Schrader. Modeling and solving an airline schedule generation problem. Annals of Operations Research, 107:117–142, 2001.
FAA. Federal Aviation Regulations. URL: http://www.faa.gov/avr/afs, 2002.
M. Gamache and F. Soumis. A method for optimally solving the rostering problem. In G. Yu, editor, Operations Research in the Airline Industry, pages 124–157. Kluwer Academic Publishers, 1998.
R. Gopalan and K. Talluri. The aircraft maintenance routing problem. Operations Research, 46(2):260–271, 1998.
C. Hane, C. Barnhart, E. Johnson, R. Marsten, G. Nemhauser, and G. Sigismondi. The fleet assignment problem: Solving a large-scale integer program. Mathematical Programming, 70:211–232, 1995.
D. Klabjan, E. Johnson, G. Nemhauser, E. Gelman, and S. Ramaswamy. Airline crew scheduling with time windows and plane count constraints. Transportation Science, 36(3):337–348, 2002.
Z. Liang and W. Chaovalitwongse. Novel network based model for aircraft maintenance routing problem. Technical report, Rutgers University, Industrial & Systems Engineering Department, 2007.
V. Mak and N. Boland. Heuristic approaches to the asymmetric travelling salesman problem with replenishment arcs. International Transactions in Operational Research, 7:431–447, 2000.
A. Mercier, J. Cordeau, and F. Soumis. A computational study of Benders decomposition for integrated aircraft routing and crew scheduling problem. Computer & Operations Research, 32:1451–1476, 2005.
A. Mercier and F. Soumis. An integrated aircraft routing, crew scheduling and flight retiming model. Computer & Operations Research, 34:2251–2265, 2007.
R. L. Phillips, D.W. Boyd, and T.A. Grossman. An algorithm for calculating consistent itinerary flows. Transportation Science, 25:225–239, 1991.
D. Ryan and B. Foster. An integer programming approach to scheduling. In A. Wren, editor, Computer Scheduling of Public Transport: Urban Passenger Vehicle and Crew Scheduling, pages 269–280. North-Holland, 1981.
A. Sarac, R. Batta, and C. Rump. A branch-and-price approach for operational aircraft maintenance routing. European Journal of Operational Research, 175:1850–1869, 2006.
H. Sherali, E. Bish, and X. Zhu. Airline fleet assignment concepts, models and algorithms. European Journal of Operational Research, 172:1–30, 2006.
C. Sriram and A. Haghani. An optimization model for aircraft maintenance scheduling and re-assignment. Transportation Research Part A, 37:29–48, 2003.
K. Talluri. The four-day aircraft maintenance routing problem. Transportation Science, 32(1):43–53, 1998.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag US
About this chapter
Cite this chapter
Liang, Z., Chaovalitwongse, W.A. (2009). The Aircraft Maintenance Routing Problem. In: Chaovalitwongse, W., Furman, K., Pardalos, P. (eds) Optimization and Logistics Challenges in the Enterprise. Springer Optimization and Its Applications, vol 30. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-88617-6_12
Download citation
DOI: https://doi.org/10.1007/978-0-387-88617-6_12
Published:
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-88616-9
Online ISBN: 978-0-387-88617-6
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)