LI Jin-lin, XU Li-ping. Capacity control models and approaches in airline network[J]. Journal of Traffic and Transportation Engineering, 2009, 9(1): 100-108. doi: 10.19818/j.cnki.1671-1637.2009.01.021
Citation: LI Jin-lin, XU Li-ping. Capacity control models and approaches in airline network[J]. Journal of Traffic and Transportation Engineering, 2009, 9(1): 100-108. doi: 10.19818/j.cnki.1671-1637.2009.01.021

Capacity control models and approaches in airline network

doi: 10.19818/j.cnki.1671-1637.2009.01.021
More Information
  • Author Bio:

    LI Jin-lin(1955-), male, professor, +86-10-68912482, jinlinli@bit.edu.cn

  • Received Date: 2008-09-01
  • Publish Date: 2009-02-25
  • In order to improve the revenue management capability of transport network system, the problem of network capacity control in strategies, models and methods was studied systematically under the background of airline network, three kinds of network control strategies were discussed such as partition booking limits, virtual nesting control and bid price control. Traditional network models and new sophisticated models were analyzed, and the new models were classified as stochastic dynamic program model, hybrid model, stochastic dynamic program model with multiple stages, and Scenario tree model. The approaches based on resources decomposition were studied. It was pointed that for constructing the network strategy, both the principle of decomposition and the single-leg capacity control model should be jointly considered. Analysis result indicates that the models and approaches of network capacity control must be efficiently combined with correct control strategies to achieve the maximum expected total revenue. 31 refs.

     

  • loading
  • [1]
    TALLURI K T, RYZI N G J. The Theory and Practice of Revenue Management[M]. Massachusetts: Kluwer Academic Publishers, 2004.
    [2]
    SECOMANDI N. An analysis of the control-algorithmresol-vingissue in finite-horizon dynamic resource allocation prob-lems[R]. Pittsburgh: Carnegie Mellon University, 2004.
    [3]
    CHEN Li-jian, HOMEM D M T. Multistage stochastic pro-gramming models for airline revenue management[R]. Evan-ston: Northwestern University, 2004.
    [4]
    M LLER A, WERNER R, WEBER K. A newapproach to O & amp; amp; D revenue management based on scenario trees[J]. Journal of Revenue and Pricing Management, 2004, 3(3): 265-276. doi: 10.1057/palgrave.rpm.5170113
    [5]
    COOPER WL, HOMEM D M T. Revenue management using sampling-based opti mization and Markov decision processes[R]. Columbus: Ohio State University, 2002.
    [6]
    BELOBABA P P. Air travel demand and airline seat inventory management[D]. Cambridge: MIT, 1987.
    [7]
    SMITHB C, LEI MUKUHLERJ F, DARROWR M. Yield management at American airlines[J]. Interfaces, 1992, 22(1): 8-31. doi: 10.1287/inte.22.1.8
    [8]
    WILLI AMSON E L. Comparison of opti mization techniques for origin-destination seat inventory control[D]. Cambridge: MIT, 1988.
    [9]
    CURRY R E. Opti mal airline seat allocation withfare classes nested by origins and destinations[J]. Transportation Sci-ence, 1990, 24(3): 193-204. doi: 10.1287/trsc.24.3.193
    [10]
    SMITHB C, PENN C W. Analysis of alternative origin-des-tination control strategies[J]. Operations Research, 1988, 40: 26-37.
    [11]
    BERTSI MAS D J, POPESCUI. Revenue management in a dynamic network environment[J]. Transportation Science, 2003, 37(3): 257-277. doi: 10.1287/trsc.37.3.257.16047
    [12]
    TALLURI K T, RYZI N G. An analysis of bid-price controls for network revenue management[J]. Management Science, 1998, 44(11): 1577-1593.
    [13]
    GLOVER F, GLOVER R, LORENZOJ, et al. The passen-ger mix problem in the scheduled airlines[J]. Interfaces, 1982, 12(3): 73-79. doi: 10.1287/inte.12.3.73
    [14]
    COOPER W L. Asymptotic behavior of an allocation policy for revenue management[J]. Operations Research, 2002, 50(4): 720-727. doi: 10.1287/opre.50.4.720.2855
    [15]
    TALLURI K T, RYZI N G. A randomized linear program-ming method for computing network bid prices[J]. Trans-portation Science, 1999, 33(2): 207-216. doi: 10.1287/trsc.33.2.207
    [16]
    CIANCI MINO A, INZERILLO G, LUCIDI S, et al. A mathe-matical programming approach for the solution of the rail way yield management problem[J]. Transportation Science, 1999, 33(2): 168-181. doi: 10.1287/trsc.33.2.168
    [17]
    BIRGEJ R, LOUVEAUX F. Introduction to Stochastic Pro-gramming[M]. Berlin: Springer-Verlag, 1997.
    [18]
    FAN Wei, CHEN Zeng-qiang, YUAN Zhu-zhi. Genetic algorithmfor airline seat inventory control[J]. Mathematics in Practice and Theory, 2004, 34(4): 38-43. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-SSJS200404007.htm
    [19]
    GAO Qiang, ZHU Jin-fu, CHEN Ke-jia. Multi-leg seat in-ventory control model for airline revenue management[J]. Journal of Traffic and Transportation Engineering, 2005, 5(4): 82-85. (in Chinese) doi: 10.3321/j.issn:1671-1637.2005.04.017
    [20]
    WILLI AMSON E L. Airline network seat control[D]. Cam-bridge: MIT, 1992.
    [21]
    BOER D S, FRELI NG R, PIERSMA N. Mathematical pro-gramming for network revenue management[J]. European Journal of Operations Research, 2002, 137(1): 72-92. doi: 10.1016/S0377-2217(01)00096-0
    [22]
    COOPER WL, HOMEN D MT. Aclass of hybrid methods for revenue management[R]. Minneapolis: University of Minnesota, 2006.
    [23]
    CHEN V C P, G NTHER D, JOHNSON E L. Solving for an opti mal airline yield management policy via statistical learning[J]. Journal of the Royal Statistical Society, 2003, 52(1): 19-30.
    [24]
    G NTHER D. Airline yield management[D]. Atlanta: Georgia Institute of Technology, 1998.
    [25]
    SIDDAPPAS, G NTHER D, ROSENBERGERJ M, et al. A statistical modeling approach to airline revenue management[R]. Arlington: The University of Texas at Arlington, 2006.
    [26]
    DEMIGUEL V, MISHRA N. A multistage stochastic pro-gramming approach to network revenue management[R]. London: London Business School, 2006.
    [27]
    BRATUS. Network value concept in airline revenue manage-ment[D]. Cambridge: MIT, 1999.
    [28]
    RYZI N G J, VULCANO G. A stochastic subgradient algo-rithmfor network capacity control[R]. New York: Columbia University, 2002.
    [29]
    BERTSI MAS D J, BOER D S. A stochastic booking li mit policy for airline network revenue management[R]. Cam-bridge: MIT, 2001.
    [30]
    MAGLARAS C, MEISSNER J. Dynamic pricing strategies for multiproduct revenue management problems[J]. Manu-facturing and Service Operations Management, 2006, 8(2): 136-148. doi: 10.1287/msom.1060.0105
    [31]
    LI Xiao-hua, XIAO Bai-chun. Comprehensive analysis of pricing and seat inventory control in airline revenue management[J]. Journal of Management Sciencein China, 2004, 7(6): 63-69. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JCYJ200406008.htm

Catalog

    Article Metrics

    Article views (543) PDF downloads(702) Cited by()
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return