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

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, Isabel, Miranda Bront, Juan José, Vulcano, Gustavo José, Zabala, Paula
Publicado: 2012
Materias:
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_0166218X_v_n_p_MendezDiaz
http://hdl.handle.net/20.500.12110/paper_0166218X_v_n_p_MendezDiaz
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spelling paper:paper_0166218X_v_n_p_MendezDiaz2023-06-08T15:15:38Z A branch-and-cut algorithm for the latent-class logit assortment problem Méndez Díaz, Isabel Miranda Bront, Juan José Vulcano, Gustavo José Zabala, Paula 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. 2012 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_0166218X_v_n_p_MendezDiaz 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)
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, Isabel
Miranda Bront, Juan José
Vulcano, Gustavo José
Zabala, Paula
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.
author Méndez Díaz, Isabel
Miranda Bront, Juan José
Vulcano, Gustavo José
Zabala, Paula
author_facet Méndez Díaz, Isabel
Miranda Bront, Juan José
Vulcano, Gustavo José
Zabala, Paula
author_sort Méndez Díaz, Isabel
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
publishDate 2012
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_0166218X_v_n_p_MendezDiaz
http://hdl.handle.net/20.500.12110/paper_0166218X_v_n_p_MendezDiaz
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