Anton J. Kleywegt, Hongzhang Shao
arXiv 10 Apr 2022 · Mathematics — Optimization · 3 citations (OpenAlex)
arXiv:2204.04774 · PDF · DOI · OpenAlex · Extracted main text
Finding the optimal product prices and product assortment are two fundamental problems in revenue management. Usually, a seller needs to jointly determine the prices and assortment while managing a network of resources with limited capacity. However, there is not yet a tractable method to efficiently solve such a problem. Existing papers studying static joint optimization of price and assortment cannot incorporate resource constraints. Then we study the revenue management problem with resource constraints and price bounds, where the prices and the product assortments need to be jointly determined over time. We showed that under the Markov chain (MC) choice model (which subsumes the multinomial logit (MNL) model), we could reformulate the choice-based joint optimization problem as a tractable convex conic optimization problem. We also proved that an optimal solution with a constant price vector exists even with constraints on resources. In addition, a solution with both constant assortment and price vector can be optimal when there is no resource constraint.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | James Dong, A Serdar Simsek, and Huseyin Topaloglu (2019) Pricing Problems under the Markov Chain Choice Model | 1.000 | 15 | 4 | 100% |
| 2 | Jacob B Feldman and Huseyin Topaloglu (2017) Revenue Management under the Markov Chain Choice Model | 1.000 | 13 | 4 | 100% |
| 3 | James Davis, Guillermo Gallego, and Huseyin Topaloglu (2013) Assortment Planning under the Multinomial Logit Model with Totally Unimodular Constraint Structures | 0.874 | 6 | 2 | 100% |
| 4 | Ruxian Wang (2012) Joint Optimization of Assortment Selection and Pricing under the Capacitated Multinomial Logit Choice Model with Product-Differe… | 0.874 | 6 | 2 | 100% |
| 5 | Guillermo Gallego and Huseyin Topaloglu (2014) Constrained Assortment Optimization for the Nested Logit Model | 0.874 | 5 | 2 | 100% |
| 6 | Yanqiao Wang and Zuo-Jun Max Shen (2017) Joint optimization of capacitated assortment and pricing problem under the tree logit model | 0.874 | 5 | 2 | 100% |
| 7 | Philipp W Keller, Retsef Levi, and Georgia Perakis (2014) Efficient Formulations for Pricing Under Attraction Demand Models | 0.811 | 4 | 2 | 100% |
| 8 | Hongmin Li and Woonghee Tim Huh (2011) Pricing Multiple Products with the Multinomial Logit and Nested Logit Models: Concavity and Implications | 0.811 | 4 | 2 | 100% |
| 9 | Jose Blanchet, Guillermo Gallego, and Vineet Goyal (2016) A Markov Chain Approximation to Choice Modeling | 0.737 | 3 | 2 | 100% |
| 10 | Guillermo Gallego, Richard Ratliff, and Sergey Shebalov (2011) A General Attraction Model and an Efficient Formulation for the Network Revenue Management Problem | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 28 scored citations.