TY - JOUR
T1 - Mathematical programming models for revenue management under customer choice
AU - Chen, Lijian
AU - Homem-de-Mello, Tito
N1 - Funding Information:
We thank two anonymous referees for their helpful comments and suggestions. This work has been supported in part by the National Science Foundation under Grant DMI-0115385.
PY - 2010/6/1
Y1 - 2010/6/1
N2 - We study a network airline revenue management problem with discrete customer choice behavior. We discuss a choice model based on the concept of preference orders, in which customers can be grouped according to a list of options in decreasing order of preference. If a customer's preferred option is not available, the customer moves to the next choice on the list with some probability. If that option is not available, the customer moves to the third choice on the list with some probability, and so forth until either the customer has no other choice but to leave or his/her request is accepted. Using this choice model as an input, we propose some mathematical programs to determine seat allocations. We also propose a post-optimization heuristic to refine the allocation suggested by the optimization model. Simulation results are presented to illustrate the effectiveness of our method, including comparisons with other models.
AB - We study a network airline revenue management problem with discrete customer choice behavior. We discuss a choice model based on the concept of preference orders, in which customers can be grouped according to a list of options in decreasing order of preference. If a customer's preferred option is not available, the customer moves to the next choice on the list with some probability. If that option is not available, the customer moves to the third choice on the list with some probability, and so forth until either the customer has no other choice but to leave or his/her request is accepted. Using this choice model as an input, we propose some mathematical programs to determine seat allocations. We also propose a post-optimization heuristic to refine the allocation suggested by the optimization model. Simulation results are presented to illustrate the effectiveness of our method, including comparisons with other models.
KW - Discrete choice
KW - Preference order
KW - Revenue management
UR - http://www.scopus.com/inward/record.url?scp=70350704681&partnerID=8YFLogxK
U2 - 10.1016/j.ejor.2009.07.029
DO - 10.1016/j.ejor.2009.07.029
M3 - Article
AN - SCOPUS:70350704681
SN - 0377-2217
VL - 203
SP - 294
EP - 305
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 2
ER -