Passenger-Centric Slot Allocation at Schedule-Coordinated Airports

Published Online:https://doi.org/10.1287/trsc.2022.1165

References

  • Adler N, Hashai N (2005) Effect of open skies in the Middle East region. Transportation Res. Part A Policy Practice 39(10):878–894.CrossrefGoogle Scholar
  • Adler N, Njoya ET, Volta N (2018) The multi-airline p-hub median problem applied to the African aviation market. Transportation Res. Part A Policy Practice 107:187–202.CrossrefGoogle Scholar
  • Atasoy B, Salani M, Bierlaire M (2014) An integrated airline scheduling, fleeting, and pricing model for a monopolized market: An integrated airline scheduling, fleeting, and pricing model. Comput.-Aided Civil Infrastructure Engrg. 29(2):76–90.CrossrefGoogle Scholar
  • Ball M, Donohue G, Hoffman K (2006) Auctions for the safe, efficient and equitable allocation of airspace system resources. Cramton P, Shoham Y, Steinberg R, eds. Combinatorial Auctions (MIT Press, Cambridge, MA), 507–538.Google Scholar
  • Ball MO, Estes AS, Hansen M, Liu Y (2020) Quantity-contingent auctions and allocation of airport slots. Transportation. Sci. 54(4):858–881.LinkGoogle Scholar
  • Barnhart C, Fearing D, Vaze V (2014) Modeling passenger travel and delays in the national air transportation system. Oper. Res. 62(3):580–601.LinkGoogle Scholar
  • Birolini S, Cattaneo M, Malighetti P, Morlotti C (2020) Integrated origin-based demand modeling for air transportation. Transportation Res. Part E Logistics Transportation Rev. 142:102050.CrossrefGoogle Scholar
  • Birolini S, Jacquillat A, Cattaneo M, Antunes AP (2021a) Airline network planning: Mixed-integer non-convex optimization with demand-supply interactions. Transportation Res. Part B Methodological 154:100–124.CrossrefGoogle Scholar
  • Birolini S, Antunes AP, Cattaneo M, Malighetti P, Paleari S (2021b) Integrated flight scheduling and fleet assignment with improved supply-demand interactions. Transportation Res. Part B Methodological 149:162–180.CrossrefGoogle Scholar
  • Boonekamp T, Zuidberg J, Burghouwt G (2018) Determinants of air travel demand: The role of low-cost carriers, ethnic links and aviation-dependent employment. Transportation Res. Part A Policy Practice 112:18–28.CrossrefGoogle Scholar
  • Bratu S, Barnhart C (2006) Flight operations recovery: New approaches considering passenger recovery. J. Scheduling 9(3):279–298.CrossrefGoogle Scholar
  • Breiman L (2001) Random forests. Machine Learning 45(1):5–32.CrossrefGoogle Scholar
  • Brueckner JK (2002) Airport congestion when carriers have market power. Amer. Econom. Rev. 92(5):1357–1375.CrossrefGoogle Scholar
  • Cadarso L, Vaze V, Barnhart C, Marín Á (2017) Integrated airline scheduling: Considering competition effects and the entry of the high speed rail. Transportation Sci. 51(1):132–154.LinkGoogle Scholar
  • Carlin A, Park RE (1970) Marginal cost pricing of airport runway capacity. Amer. Econom. Rev. 60(3):310–319.Google Scholar
  • Daniel JI (1995) Congestion pricing and capacity of large hub airports: A bottleneck model with stochastic queues. Econometrica 63(2):327–370.CrossrefGoogle Scholar
  • Dong Z, Chuhang Y, Lau HH (2016) An integrated flight scheduling and fleet assignment method based on a discrete choice model. Comput. Indust. Engrg. 98:195–210.CrossrefGoogle Scholar
  • Fairbrother J, Zografos KG (2021) Optimal scheduling of slots with season segmentation. Eur. J. Oper. Res. 291(3):961–982.CrossrefGoogle Scholar
  • Grosche T, Rothlauf F, Heinzl A (2007) Gravity models for airline passenger volume estimation. J. Air Transport Management 13(4):175–183.CrossrefGoogle Scholar
  • Hakim MM, Merkert R (2016) The causal relationship between air transport and economic growth: Empirical evidence from South Asia. J. Transportation Geogr. 56:120–127.CrossrefGoogle Scholar
  • Hoerl AE, Kennard RW (1970) Ridge regression: Biased estimation for nonorthogonal problems. Technometrics 42(1):80–86.CrossrefGoogle Scholar
  • IATA (2014) Standard Schedules Information Manual (SSIM) (International Air Transport Association, Montreal).Google Scholar
  • IATA (2020) Worldwide Airport Slot Guidelines (International Air Transport Association, Montreal).Google Scholar
  • Jacquillat A (2020) Predictive and Prescriptive Analytics toward Passenger-centric Ground Delay Programs. Preprint, submitted November 20, https://dx.doi.org/10.2139/ssrn.3734008.Google Scholar
  • Jacquillat A, Vaze V (2018) Interairline equity in airport scheduling interventions. Transportation Sci. 52(4):941–964.LinkGoogle Scholar
  • Jiang Y, Zografos KG (2021) A decision making framework for incorporating fairness in allocating slots at capacity-constrained airports. Transportation Res. Part C Emerging Tech. 126:103039.CrossrefGoogle Scholar
  • Jin F, Li Y, Sun S, Li H (2020) Forecasting air passenger demand with a new hybrid ensemble approach. J. Air Transportation Management 83:101744.CrossrefGoogle Scholar
  • Jorge D, Ribeiro NA, Antunes AP (2021) Towards a decision-support tool for airport slot allocation: Application to Guarulhos (Sao Paulo, Brazil). J. Air Transportation Management 93:102048.CrossrefGoogle Scholar
  • Katsigiannis FA, Zografos KG (2021) Optimising airport slot allocation considering flight-scheduling flexibility and total airport capacity constraints. Transportation Res. Part B Methodological 146:50–87.CrossrefGoogle Scholar
  • Katsigiannis FA, Zografos KG, Fairbrother J (2021) Modelling and solving the airport slot-scheduling problem with multi-objective, multi-level considerations. Transportation Res. Part C Emerging Tech. 124:102914.CrossrefGoogle Scholar
  • Lhéritier A, Bocamazo M, Delahaye T, Acuna-Agost R (2019) Airline itinerary choice modeling using machine learning. J. Choice Model. 31:198–209.CrossrefGoogle Scholar
  • Lohatepanont M, Barnhart C (2004) Airline schedule planning: Integrated models and algorithms for schedule design and fleet assignment. Transportation Sci. 38(1):19–32.LinkGoogle Scholar
  • Lundberg S, Lee SI (2017) A unified approach to interpreting model predictions. von Luxburg U, Guyon I, Bengio S, Wallach H, Fergus R, eds. NIPS'17 Proc. 31st Internat. Conf. Neural Inform. Processing Systems (Curran Associates, Red Hook, NY), 4768–4777.Google Scholar
  • Lurkin V, Garrow LA, Higgins MJ, Newman JP, Schyns M (2017) Accounting for price endogeneity in airline itinerary choice models: An application to continental US markets. Transportation Res. Part A Policy Practice 100:228–246.CrossrefGoogle Scholar
  • Marazzo M, Scherre R, Fernandes E (2010) Air transport demand and economic growth in Brazil: A time series analysis. Transportation Res. Part E Logist. Transportation Rev. 46(2):261–269.CrossrefGoogle Scholar
  • Marla L, Vaaben B, Barnhart C (2017) Integrated disruption management and flight planning to trade off delays and fuel burn. Transportation Sci. 51(1):88–111.LinkGoogle Scholar
  • Paleari S, Redondi R, Malighetti P (2010) A comparative study of airport connectivity in China, Europe and US: Which network provides the best service to passengers? Transportation Res. Part E Logistics Transportation Rev. 2:198–210.CrossrefGoogle Scholar
  • Phyoe S, Guo R, Zhong Z (2016) An air traffic forecasting study and simulation. Internat. J. Sci. Tech. 2(3):55–69.Google Scholar
  • Pita JP, Barnhart C, Antunes AP (2013) Integrated flight scheduling and fleet assignment under airport congestion. Transportation Sci. 47(4):477–492.LinkGoogle Scholar
  • Rassenti SJ, Smith VL, Bulfin RL (1982) A combinatorial auction mechanism for airport time slot allocation. Bell J. Econom. 13(2):402–417.CrossrefGoogle Scholar
  • Ribeiro NA, Jacquillat A, Antunes AP (2019) A large-scale neighborhood search approach to airport slot allocation. Transportation Sci. 53(6):1772–1797.LinkGoogle Scholar
  • Ribeiro NA, Jacquillat A, Antunes AP, Odoni AR, Pita JP (2018) An optimization approach for airport slot allocation under IATA guidelines. Transportation Res. Part B Methodological 112:132–156.CrossrefGoogle Scholar
  • Sherali HD, Bae KH, Haouari M (2010) Integrated airline schedule design and fleet assignment: Polyhedral analysis and benders’ decomposition approach. INFORMS J. Comput. 22(4):500–513.LinkGoogle Scholar
  • Tibshirani R (1996) Regression shrinkage and selection via the lasso. J. Roy. Statist. Soc. Ser. B Methodological 58(1):267–288.CrossrefGoogle Scholar
  • Tsui WHK, Balli HO, Gilbey A, Gow H (2014) Forecasting of Hong Kong Airport’s passenger throughput. Tourism Management 42:62–76.CrossrefGoogle Scholar
  • Wei W, Hansen M (2006) An aggregate demand model for air passenger traffic in the hub-and-spoke network. Transportation Res. Part A Policy Practice 40(10):841–851.CrossrefGoogle Scholar
  • Wei K, Vaze V, Jacquillat A (2020) Airline timetable development and fleet assignment incorporating passenger choice. Transportation Sci. 139–163.LinkGoogle Scholar
  • Zografos KG, Jiang Y (2019) A bi-objective efficiency-fairness model for scheduling slots at congested airports. Transportation Res. Part C Emerging Tech. 102:336–350.CrossrefGoogle Scholar
  • Zografos KG, Androutsopoulos KN, Madas MA (2018) Minding the gap: Optimizing airport schedule displacement and acceptability. Transportation Res. Part A Policy Practice 114:203–221.CrossrefGoogle Scholar
  • Zografos KG, Madas MA, Androutsopoulos KN (2017) Increasing airport capacity utilisation through optimum slot scheduling: Review of current developments and identification of future needs. J. Scheduling 20(1):3–24.CrossrefGoogle Scholar
  • Zografos KG, Salouras Y, Madas MA (2012) Dealing with the efficient allocation of scarce resources at congested airports. Transportation Res. Part C Emerging Tech. 21(1):244–256.CrossrefGoogle Scholar
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