Dynamic Assortment Optimization with a Multinomial Logit Choice Model and Capacity Constraint

By Paat Rusmevichientong, Zuo-Jun Max Shen, David B. Shmoys. Operational Research, 2010

487 citations recorded by the source corpus.

Subfields: Management Information Systems, Management Science and Operations Research, Marketing

View Paper: https://www.semanticscholar.org/paper/99be3a3cf9ab8d3e9b1fc83b75d2976535371e93

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Citations in the corpus

Dynamic Pricing and Learning: Historical Origins, Current Research, and New Directions (2013, unknown): “[321–323]), product launch and product exit optimization (e.”
Assortment Optimization Under General Choice (2011, methodology): “Since h i ( · ) is monotonically decreasing, it is easy to see that (5) Under appropriate technical assumptions, Rusmevichientong et al. (2010a) showed that for any 1 ≤ S ≤ N , the optimal assortment of size at most S under the MNL model is one of the assortments in the collection B S def = { B S (…”
Assortment Optimization under the Multinomial Logit Model with Random Choice Parameters (2014, background): “Rusmevichientong et al. (2010) study the same problem with a cardinality constraint on the offered assortment and show that although revenue-ordered assortments are no longer optimal, the optimal assortment can be computed efﬁciently.”
( Please , provide the manuscript number ! ) Capacity Constrained Assortment Optimization under the Markov Chain based Choice Model (2015, unknown): “Key words : Assortment optimization, choice models, approximation algorithms, Markov chain”
Assortment Optimization Under Variants of the Nested Logit Model (2014, background): “This class of assortments is known to be optimal when the customer choices are governed by the multinomial logit model and Rusmevichientong et al. (2014) give a performance guarantee for such assortments when the underlying choice model is the multinomial logit model with multiple customer types.”
A Nonparametric Approach to Modeling Choice with Limited Data (2009, methodology): “Rusmevichientong et al. (2010) consider the MNL model and provide an efficient algorithm for the static assortment optimization problem and propose an efficient policy for the dynamic optimization problem.”