New Bounds for Assortment Optimization Under the Nested Logit Model

43 Pages Posted: 2 Jul 2018

See all articles by Sumit Kunnumkal

Sumit Kunnumkal

Queen's University - Smith School of Business

Date Written: October 8, 2017

Abstract

We consider the assortment optimization problem under the nested logit model and obtain new bounds on the gap between the optimal expected revenue and an upper bound based on a certain continuous relaxation of the assortment problem. Our bounds can be tighter than the existing bounds in the literature and provide more insight into the key drivers of tractability for the assortment optimization problem under the nested logit model. Moreover, our bounds scale with the nest dissimilarity parameters and we recover the well-known tractability results for the assortment optimization problem under the multinomial logit model when all the nest dissimilarity parameters are equal to one. We extend our results to the cardinality constrained assortment problem where there are constraints that limit the number of products that can be offered within each nest.

Suggested Citation

Kunnumkal, Sumit, New Bounds for Assortment Optimization Under the Nested Logit Model (October 8, 2017). Indian School of Business, Available at SSRN: https://ssrn.com/abstract=3087537 or http://dx.doi.org/10.2139/ssrn.3087537

Sumit Kunnumkal (Contact Author)

Queen's University - Smith School of Business ( email )

Smith School of Business - Queen's University
143 Union Street
Kingston, Ontario K7L 3N6
Canada

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