A multi-objective approach for robust airline scheduling

Computers and Operations Research

Volumn 37, Issue 5, 2010, Pages 822-832

  Burke, Edmund K ^a   De Causmaecker, Patrick ^b   De Maere, Geert ^a,d   Mulder, Jeroen ^c   Paelinck, Marc ^c   Vanden Berghe, Greet ^d  

^a Nottingham University Jubilee Campus   (United Kingdom)

^b KU Leuven Campus Kortrijk   (Belgium)

^c KLM ROYAL DUTCH AIRLINES   (Netherlands)

^d Vakgroep Informatie Technologie   (Belgium)

Author keywords

Large scale simulation; Multi meme memetic algorithms; Multi objective improvement; Robust airline scheduling

Indexed keywords

ADAPTIVE GRIDS; AIRCRAFT RE-ROUTING; AIRLINE SCHEDULING; FLEET ASSIGNMENT; HIGH-QUALITY SOLUTIONS; LARGE SCALE SIMULATION; LARGE SCALE SIMULATIONS; MEMETIC ALGORITHMS; MEMETIC APPROACH; MULTI OBJECTIVE; MULTI-MEME MEMETIC ALGORITHMS; MULTI-OBJECTIVE IMPROVEMENT; OPERATIONAL PERFORMANCE; PARETO-OPTIMAL FRONT; RETIMING; ROBUST AIRLINE SCHEDULING; ROYAL DUTCH; SEARCH SPACES;

ADAPTIVE ALGORITHMS; AIRCRAFT; APPROXIMATION ALGORITHMS; EVOLUTIONARY ALGORITHMS; HUMAN COMPUTER INTERACTION; MULTIOBJECTIVE OPTIMIZATION; RELIABILITY ANALYSIS; SENSITIVITY ANALYSIS;

AIR TRANSPORTATION;

EID: 70449523353     PISSN: 03050548     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cor.2009.03.026     Document Type: Article

References (52)

1. Delays to air transport in Europe: digest annual 2005. Technical Report, Eurocontrol, 2005.
2. Eurocontrol medium-term forecast: IFR flight movements 2007-2013. Technical Report, Eurocontrol, 2006.
3. Lan S., Clarke J., and Barnhart C. Planning for robust airline operations: optimizing aircraft routings and flight departure times to minimize passenger disruptions. Transportation Science 40 (2006) 15-28
4. Rosenberger J., Johnson E., and Nemhauser G. A robust fleet-assignment model with hub isolation and short cycles. Transportation Science 38 (2004) 357-368
5. Abara J. Applying integer linear programming to the fleet assignment problem. Interfaces 19 (1989) 20-28
6. Etschmaier M., and Mathaisel D. Airline scheduling: an overview. Transportation Science 19 (1985) 127-138
7. Barnhart C., Belobaba P., and Odoni A. Applications of operations research in air transport industry. Transportation Science 37 (2003) 368-391
8. Barnhart C., and Cohn A. Airline schedule planning: accomplishments and opportunities. Manufacturing and Service Operations Management 6 (2004) 3-22
9. Gopalakrishnan B., and Johnson E. Airline crew scheduling: state-of-the-art. Annals of Operations Research 140 (2005) 305-337
10. Barnhart C., Lu F., and Shenoi R. Integrated airline schedule planning (1998), Kluwer Academic Publishers, Dordrecht [chapter 9, p. 384-403]
11. Klabjan D., Johnson E., Nemhauser G., Gelman E., and Ramaswamy S. Airline crew scheduling with time window and plane-count constraints. Transportation Science 36 (2002) 337-348
12. Clarke L., Hane C., Johnson E., and Nemhauser G. Maintenance and crew considerations in fleet assignment. Transportation Science 30 (1996) 249-260
13. Lohatepanont M., and Barnhart C. Airline schedule planning. integrated models and algorithms for schedule design and fleet assignment. Transportation Science 38 (2004) 19-32
14. Mercier A., and Soumis F. An integrated aircraft routing and crew scheduling model with time windows. Computers and Operations Research 34 (2007) 2251-2265
15. Kang L. Degradable airline scheduling: an approach to improve operational robustness and differentiate service quality. PhD thesis, Sloan School of Management, Massachusetts Institute of Technology; 2004.
16. Schaefer A., Johnson E., Kleywegt A., and Nemhauser G. Airline crew scheduling under uncertainty. Transportation Science 39 (2005) 340-348
17. Yen J., and Birge J. A stochastic programming approach to the airline crew scheduling problem. Transportation Science 40 (2006) 3-14
18. Lee L., Lee C., and Tan Y. A multi-objective genetic algorithm for robust flight scheduling using simulation. European Journal of Operational Research 117 (2007) 1948-1968
19. Bian F., Burke E., Jain S., Kendall G., Koole G., Landa-Silva J., et al. Making airline schedules more robust (2005), Springer, Berlin p. 381-92
20. Ageeva Y. Approaches to incorporate robustness into airline scheduling. Master's thesis, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology; 2000.
21. Rosenberger J. Topics in airline operations. PhD thesis, Georgia Institute of Technology, 2004.
22. Smith B. Robust airline fleet assignment. PhD thesis, Georgia Institute of Technology, 2004.
23. Smith B., and Johnson E. Robust airline fleet assignment: imposing station purity using station decomposition. Transportation Science 40 (2006) 497-516
24. Wu C., and Caves R. Towards the optimisation of the schedule reliability of aircraft rotations. Journal of Air Transport Management 8 (2002) 419-426
25. Ehrgott M., and Ryan D. Constructing robust crew schedules with bicriteria optimization. Journal of Multicriteria Decision Analysis 11 (2002) 139-150
26. Shebalov S., and Klabjan D. Robust airline crew pairing: move-up crew. Transportation Science 40 (2006) 300-312
27. Deb K. Multi-objective optimization using evolutionary algorithms (2001), Wiley, New York
28. Landa Silva J., Burke E., and Petrovic S. An introduction to multiobjective metaheuristics for scheduling and timetabling. Lecture notes in economics and mathematical systems vol. 535 (2004), Springer, Berlin [chapter 4, p. 91-129]
29. Deb K. Multi-objective optimization (2005), Springer, Berlin [chapter 10, p. 273-316]
30. Subramanian R., Scheff R., Quillinan J., Wiper S., and Marsten R. Cold start fleet assignment at delta air lines. Interfaces 24 (1994) 104-120
31. Hane C., Johnson E., Marsten R., Nemhauser G., and Sigismondi G. The fleet assignment problem: solving a large-scale integer program. Mathematical Programming 70 (1995) 211-232
32. Rushmeier R., and Kontogiorgis S. Advances in the optimization of airline fleet assignment. Transportation Science 31 (1997) 159-169
33. Stewart T, Strijbosch L, Moors J, Batenburg PV. A simple approximation to the convolution of gamma distributions, center discussion paper, int. rep. 2006-27. Technical Report, University of Tilburg, 2006.
34. Ishibuchi H., and Murata T. A multi-objective genetic local search algorithm and its applications to flow shop scheduling. IEEE Transactions on Evolutionary Computation 28 (1998) 392-403
35. Jaszkiewicz A. Genetic local search for multi-objective combinatorial optimization. European Journal of Operational Research 137 (2002) 50-71
36. Sinha A., Chen Y., and Goldberg D. Designing efficient genetic and evolutionary algorithm hybrids (2005), Springer, Berlin [chapter 12, p. 259-88]
37. Krasnogor N., and Smith J. A tutorial for competent memetic algorithms: model and taxonomy and design issues. IEEE Transactions on Evolutionary Computation 9 (2005) 474-488
38. Miettinen K. Nonlinear multiobjective optimisation (1999), Kluwer Academic Publishers, Boston, MA
39. Ehrgott M. Multicriteria optimization. 2nd ed (2005), Springer, Berlin
40. Sastry K., Goldberg D., and Kendall G. Genetic algorithms (2005), Springer, Berlin [chapter 4, p. 97-126]
41. Burke E., and Landa-Silva J. The design of memetic algorithms for scheduling and timetabling problems (2004), Springer, Berlin [chapter 13, p. 289-312]
42. Ishibuchi H., Yoshida T., and Murata T. Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling. IEEE Transactions on Evolutionary Computation 7 (2003) 204-223
43. Ishibuchi H, Narukawa K. Performance evaluation of simple multiobjective genetic local search algorithms on multiobjective 0/1 knapsack problems. In: Proceedings of the 2004 congress on evolutionary computation (CEC 2004), IEEE Press, 2004. p. 441-48.
44. Krasnogor N., Blackburne B., Burke E., and Hirst J. Multimeme algorithms for protein structure prediction. Parallel problem solving from Nature-PPSN VII: seventh international conference (2002), Springer, Berlin/Heidelberg 769-788
45. Ong Y., and Keane A. Meta-Lamarckian learning in memetic algorithms. IEEE Transactions on Evolutionary Computation 8 (2004) 99-110
46. Alkan A, Ozcan E. Memetic algorithms for timetabling. In: Proceedings of 2003 IEEE congress on evolutionary computation, 2003. p. 1796-1802.
47. Ozcan E. An empirical investigation on memes, self-generation and nurse rostering. In: Proceedings of the 6th international conference on the practice and theory of automated timetabling, 2006. p. 246-63.
48. Whitley D, Starkweather T, Fuquay D. Scheduling problems and the travelling salesman: the genetic edge recombination operator. In: Proceedings of the third international conference on genetic algorithms and their applications, 1989. p. 133-40.
49. Knowles J., and Corne D. Properties of an adaptive archiving algorithm for storing nondominated vectors. IEEE Transactions on Evolutionary Computation 7 (2003) 100-116
50. High performance computing, main cluster specifications, On-line resource, available at: 〈http://www.nottingham.ac.uk/hpc/html/facility/specifications/index .php〉.
51. Zitzler E. Evolutionary algorithms for multiobjective optimization: methods and applications. PhD thesis, ETH Zurich, Switzerland; 1999.
52. Jacobs P, Verbraeck A, Mulder J. Flight scheduling at KLM. In: Proceedings of the winter simulation conference, 2005. p. 299-306.