On the Choice-Based Linear Programming Model for Network Revenue Management

  • Authors:

  • Qian Liu;Garrett van Ryzin

  • Affiliations:

  • Industrial Engineering and Logistics Management Department, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong;Graduate School of Business, Columbia University, New York, New York 10027

  • Venue:
  • Manufacturing & Service Operations Management
  • Year:
  • 2008

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Abstract

Gallego 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.