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

By Qian Liu, G. V. Ryzin. Manufacturing & Service Operations Management, 2008

416 citations recorded by the source corpus.

Subfields: Management Information Systems, Marketing, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/a40b3538101675a77b268c463416eb2b68d69b94

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Citations in the corpus

Assortment Planning Under the Multinomial Logit Model with Totally Unimodular Constraint Structures (2013, background): “So, it is enough to show that problems (3) and (4) are equivalent to each other, which is what we do in the rest of the proof.”
Dynamic Assortment Optimization with a Multinomial Logit Choice Model and Capacity Constraint (2010, methodology): “The static assortment planning (where the underlying demand distribution is assumed be known in advance) has an extensive literature, and we refer the reader to Kok et al. (2008) for an excellent review of the current state of the art.”
Assortment Optimization under the Multinomial Logit Model with Random Choice Parameters (2014, background): “There are a number of articles that extend this work to a ﬂight network; see Gallego et al. (2004), Liu and van Ryzin (2008), Kunnumkal and Topaloglu (2008), Zhang and Adelman (2009), Talluri (2010), Gallego et al. (2011), Meissner and Strauss (2012), Vossen and Zhang (2012), and Meiss-ner et al.…”
Joint Stocking and Product Offer Decisions Under the Multinomial Logit Model (2013, background): “Liu and van Ryzin (2008) give a dynamic programming formulation for network revenue management problems and approximately solve the dynamic program by decomposing it by the ﬂight legs.”
Assortment Optimization Under Variants of the Nested Logit Model (2014, methodology): “To advance this agenda, researchers have developed discrete choice models based on axioms as in Luce (1959), resulting in the basic attraction model, and based on random utility theory as in McFadden (1974), resulting in the celebrated multinomial logit model.”
Intertemporal Pricing with Strategic Customer Behavior (2007, background): “Talluri and van Ryzin (2004) use discrete choice models to describe how customers, in the context of airlines, choose among the set of fare classes offered; van Ryzin and Liu (2004) extends this analysis to the network setting.”
Customer Behavior Modeling in Revenue Management and Auctions: A Review and New Research Opportunities (2007, background): “The main ﬁnding here is that many seemingly reasonable assumptions in the research papers may not hold in practice, so extra care must be paid when designing and implementing real-life auctions.”