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Stochastic programming in revenue management

Chen, Lijian
http://rave.ohiolink.edu/etdc/view?acc_num=osu1150314352

Abstract Details

2006, Doctor of Philosophy, Ohio State University, Industrial and Systems Engineering.
Airline revenue management aims to assign the right seat to the right customer with right prices at the right time. Due to the existence of large uncertainty in customer demand and the unavailability of perfect information, decisions must be made in advance. Also, such decisions are subject to constraints, such as seat availability, demand forecasts, and customer preferences. The objective of revenue management is to maximize the long term booking revenue. In this research, we studied two models in detail, the seat allocation model and the customer choice model based on preference orders. The seat allocation model is to decide the number of seats available for booking at class level by assuming the demands among booking classes are independent. The customer choice model is to assign seats at class level without forecasting demands individually. Both research topics in revenue management, the seat allocation optimization and customer choice optimization, are built by stochastic programming models. We present a multi-stage stochastic programming formulation to the seat allocation problem that extends the traditional probabilistic model proposed in the literature. Because of the lack of convexity properties, solving the multi-stage problem exactly may be difficult. In order to circumvent that obstacle, we use an approximation based on solving a sequence of two-stage stochastic programs with simple recourse. Our theoretical results show that the proposed approximation is robust, in the sense that solving more successive two-stage programs can only improve the expected revenue. We also discuss a heuristic method to choose the re-solving points. Numerical results are presented to illustrate the effectiveness of the proposed approach.
Clark Mount-Campbell (Advisor)
123 p.
Engineering, Industrial

Recommended Citations

Citations

  • Chen, L. (2006). Stochastic programming in revenue management [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1150314352

    APA Style (7th edition)

  • Chen, Lijian. Stochastic programming in revenue management. 2006. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1150314352.

    MLA Style (8th edition)

  • Chen, Lijian. "Stochastic programming in revenue management." Doctoral dissertation, Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=osu1150314352

    Chicago Manual of Style (17th edition)

osu1150314352
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© 2006, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.