Managing Flexible Products on a Network

By Guillermo Gallego, Garud N. Iyengar, R. Phillips, A. Dubey. 2005

294 citations recorded by the source corpus.

Subfields: Management Information Systems, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/9917ccfe4166185b5de2cca4f1b5aea18b0f3caa

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In Management Information Systems

In Strategy and Management

Citations in the corpus

A Nonparametric Approach to Modeling Choice with Limited Data (2009, methodology): “The origins of the MNL model date all the way back to the Plackett– Luce model, proposed independently by Luce (1959) and Plackett (1975). Before becoming popular in the area of OM, the MNL model found widespread use in the areas of transportation (see seminal works of McFadden 1980 and Ben-Akiva an”
A Column Generation Algorithm for Choice-Based Network Revenue Management (2009, background): “[6], and the follow-up dynamic programming (DP) decomposition heuristic of van Ryzin and Liu [16], and focus on the more general version of these models, where customers belong to overlapping segments.”
Assortment Planning Under the Multinomial Logit Model with Totally Unimodular Constraint Structures (2013, methodology): “This model was proposed by Gallego et al. (2011) and involves a shadow attraction value for each product that impinges on the choice probabilities when the products are not offered.”
Joint Stocking and Product Offer Decisions Under the Multinomial Logit Model (2013, background): “the linear program proposed by Gallego et al. (2004), Bront, Diaz and Vulcano (2009) consider the case where there are multiple customer types that make a choice according to multinomial logit models with different parameters. Gallego et al. (2011) focus on the same linear program and show how to re”
On the Choice-Based Linear Programming Model for Network Revenue Management (2008, methodology): “Nevertheless, as shown by Gallego et al. (2004) and as discussed further in §6 below, columngeneration techniques can be used to try to solve this LP efficiently.”
Customer Behavior Modeling in Revenue Management and Auctions: A Review and New Research Opportunities (2007, methodology): “They show that this approximation yields tighter bounds on the value function compared with the choice-based linear programming approach of Liu and van Ryzin (2007a) and Gallego et al. (2004).”
Dynamic Assortment Optimization with a Multinomial Logit Choice Model and Capacity Constraint (2010, methodology): “As shown in the following example, in contrast to the unconstrained problem (Gallego et al., 2004; Liu and van Ryzin, 2008), a greedy policy that sequentially adds one product to an assortment (until the profit decreases) may lead to a suboptimal solution when we have a capacity constraint.”
Assortment Optimization under the Multinomial Logit Model with Random Choice Parameters (2014, background): “There are a number of papers 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.”
Assortment Optimization Under Variants of the Nested Logit Model (2014, methodology): “Gallego et al. (2004), Liu and van Ryzin (2008), Kunnumkal and Topaloglu (2008), Zhang and Adelman (2009) and Bront et al. (2009) extend this model to a flight network.”