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Network revenue management with inventory-sensitive bid prices and customer choice

  • Meissner, Joern
  • Strauss, Arne

We develop an approximate dynamic programming approach to network revenue management models with customer choice that approximates the value function of the Markov decision process with a non-linear function which is separable across resource inventory levels. This approximation can exhibit significantly improved accuracy compared to currently available methods. It further allows for arbitrary aggregation of inventory units and thereby reduction of computational workload, yields upper bounds on the optimal expected revenue that are provably at least as tight as those obtained from previous approaches. Computational experiments for the multinomial logit choice model with distinct consideration sets show that policies derived from our approach can outperform some recently proposed alternatives, and we demonstrate how aggregation can be used to balance solution quality and runtime.

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Article provided by Elsevier in its journal European Journal of Operational Research.

Volume (Year): 216 (2012)
Issue (Month): 2 ()
Pages: 459-468

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Handle: RePEc:eee:ejores:v:216:y:2012:i:2:p:459-468
Contact details of provider: Web page: http://www.elsevier.com/locate/eor

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  1. Joern Meissner & Arne Strauss & Kalyan Talluri, 2011. "An Enhanced Concave Program Relaxation for Choice Network Revenue Management," Working Papers MRG/0020, Department of Management Science, Lancaster University, revised Jan 2011.
  2. Zhang, Dan & Cooper, William L., 2009. "Pricing substitutable flights in airline revenue management," European Journal of Operational Research, Elsevier, vol. 197(3), pages 848-861, September.
  3. Garrett van Ryzin & Gustavo Vulcano, 2008. "Computing Virtual Nesting Controls for Network Revenue Management Under Customer Choice Behavior," Manufacturing & Service Operations Management, INFORMS, vol. 10(3), pages 448-467, October.
  4. Wen-Chyuan Chiang & Jason C.H. Chen & Xiaojing Xu, 2007. "An overview of research on revenue management: current issues and future research," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 1(1), pages 97-128.
  5. Joern Meissner & Arne Strauss, 2009. "Choice-Based Network Revenue Management under Weak Market Segmentation," Working Papers MRG/0012, Department of Management Science, Lancaster University, revised May 2010.
  6. Kalyan Talluri & Garrett van Ryzin, 2004. "Revenue Management Under a General Discrete Choice Model of Consumer Behavior," Management Science, INFORMS, vol. 50(1), pages 15-33, January.
  7. Chen, Lijian & Homem-de-Mello, Tito, 2010. "Mathematical programming models for revenue management under customer choice," European Journal of Operational Research, Elsevier, vol. 203(2), pages 294-305, June.
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