A branch-and-cut algorithm for the latent-class logit assortment problem

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We study the product assortment problem of a retail operation that faces a stream of customers who are heterogeneous with respect to preferences. Each customer belongs to a market segment characterized by a consideration set that includes the alternatives viewed as options, and by the preference wei...

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Autores principales: Méndez-Díaz, I., Miranda-Bront, J.J., Vulcano, G., Zabala, P.
Formato: INPR
Lenguaje:English
Materias:
Choice behavior
Fractional programming
Integer programming
Multinomial logit
Retail operations
Revenue management
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_0166218X_v_n_p_MendezDiaz
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Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
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spelling todo:paper_0166218X_v_n_p_MendezDiaz2023-10-03T15:03:48Z A branch-and-cut algorithm for the latent-class logit assortment problem Méndez-Díaz, I. Miranda-Bront, J.J. Vulcano, G. Zabala, P. Choice behavior Fractional programming Integer programming Multinomial logit Retail operations Revenue management We study the product assortment problem of a retail operation that faces a stream of customers who are heterogeneous with respect to preferences. Each customer belongs to a market segment characterized by a consideration set that includes the alternatives viewed as options, and by the preference weights that the segment assigns to each of those alternatives. Upon arrival, he checks the offer set displayed by the firm, and either chooses one of those products or quits without purchasing according to a multinomial-logit (MNL) criterion. The firm's goal is to maximize the expected revenue extracted during a fixed time horizon. This problem also arises in the growing area of choice-based, network revenue management, where computational speed is a critical factor for the practical viability of a solution approach. This so-called latent-class, logit assortment problem is known to be NP-Hard. In this paper, we analyze unconstrained and constrained (i.e., with a limited number of products to display) versions of it, and propose a branch-and-cut algorithm that is computationally fast and leads to (nearly) optimal solutions. © 2012 Elsevier B.V. All rights reserved. Fil:Méndez-Díaz, I. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Miranda-Bront, J.J. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Vulcano, G. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Zabala, P. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. INPR English info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_0166218X_v_n_p_MendezDiaz
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
language English
orig_language_str_mv English
topic Choice behavior
Fractional programming
Integer programming
Multinomial logit
Retail operations
Revenue management
spellingShingle Choice behavior
Fractional programming
Integer programming
Multinomial logit
Retail operations
Revenue management
Méndez-Díaz, I.
Miranda-Bront, J.J.
Vulcano, G.
Zabala, P.
A branch-and-cut algorithm for the latent-class logit assortment problem
topic_facet Choice behavior
Fractional programming
Integer programming
Multinomial logit
Retail operations
Revenue management
description We study the product assortment problem of a retail operation that faces a stream of customers who are heterogeneous with respect to preferences. Each customer belongs to a market segment characterized by a consideration set that includes the alternatives viewed as options, and by the preference weights that the segment assigns to each of those alternatives. Upon arrival, he checks the offer set displayed by the firm, and either chooses one of those products or quits without purchasing according to a multinomial-logit (MNL) criterion. The firm's goal is to maximize the expected revenue extracted during a fixed time horizon. This problem also arises in the growing area of choice-based, network revenue management, where computational speed is a critical factor for the practical viability of a solution approach. This so-called latent-class, logit assortment problem is known to be NP-Hard. In this paper, we analyze unconstrained and constrained (i.e., with a limited number of products to display) versions of it, and propose a branch-and-cut algorithm that is computationally fast and leads to (nearly) optimal solutions. © 2012 Elsevier B.V. All rights reserved.
format INPR
author Méndez-Díaz, I.
Miranda-Bront, J.J.
Vulcano, G.
Zabala, P.
author_facet Méndez-Díaz, I.
Miranda-Bront, J.J.
Vulcano, G.
Zabala, P.
author_sort Méndez-Díaz, I.
title A branch-and-cut algorithm for the latent-class logit assortment problem
title_short A branch-and-cut algorithm for the latent-class logit assortment problem
title_full A branch-and-cut algorithm for the latent-class logit assortment problem
title_fullStr A branch-and-cut algorithm for the latent-class logit assortment problem
title_full_unstemmed A branch-and-cut algorithm for the latent-class logit assortment problem
title_sort branch-and-cut algorithm for the latent-class logit assortment problem
url http://hdl.handle.net/20.500.12110/paper_0166218X_v_n_p_MendezDiaz
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