On the choice-based linear programming model for network revenue management

成果类型:
Article
署名作者:
Liu, Qian; van Ryzin, Garrett
署名单位:
Hong Kong University of Science & Technology; Columbia University
刊物名称:
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
ISSN/ISSBN:
1523-4614
DOI:
10.1287/msom.1070.0169
发表日期:
2008
页码:
288-310
关键词:
Network Revenue Management choice behavior multinomial logit choice model dynamic programming linear programming
摘要:
G allego et al. [Gallego, G., G. Iyengar, R. Phillips, A. Dubey. 2004. Managing flexible products on a network. CORC Technical Report TR-2004-01, Department of Industrial Engineering and Operations Research, Columbia University, New York.] recently proposed a choice-based deterministic linear programming model (CDLP) for network revenue management (RM) that parallels the widely used deterministic linear programming (DLP) model. While they focused on analyzing flexible products-a situation in which the provider has the flexibility of using a collection of products (e. g., different flight times and/or itineraries) to serve the same market demand (e. g., an origin-destination connection)-their approach has broader implications for understanding choice-based RM on a network. In this paper, we explore the implications in detail. Specifically, we characterize optimal offer sets (sets of available network products) by extending to the network case a notion of efficiency developed by Talluri and van Ryzin [Talluri, K. T., G. J. van Ryzin. 2004. Revenue management under a general discrete choice model of consumer behavior. Management Sci. 50 15-33.] for the single-leg, choice-based RM problem. We show that, asymptotically, as demand and capacity are scaled up, only these efficient sets are used in an optimal policy. This analysis suggests that efficiency is a potentially useful approach for identifying good offer sets on networks, as it is in the case of single-leg problems. Second, we propose a practical decomposition heuristic for converting the static CDLP solution into a dynamic control policy. The heuristic is quite similar to the familiar displacement-adjusted virtual nesting (DAVN) approximation used in traditional network RM, and it significantly improves on the performance of the static LP solution. We illustrate the heuristic on several numerical examples.