Designing e‐commerce supply chains: a stochastic facility–location approach

E‐Commerce activity has been increasing during recent years, and this trend is expected to continue in the near future. e‐Commerce practices are subject to uncertainty conditions and high variability in customers’ demands. Considering these characteristics, we propose two facility–location models th...

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Detalles Bibliográficos
Autores: Pagès Bernaus, Adela, Ramalhinho-Lourenço, Helena, Juan, Angel A., Calvet Mir, Laura
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2017
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/44394
Acceso en línea:http://hdl.handle.net/10230/44394
http://dx.doi.org/10.1111/itor.12433
Access Level:acceso abierto
Palabra clave:E-commerce
Supply chain management
Capacitated facility location problem
Stochastic combinatorial optimization
Simheuristics
Stochastic programming
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spelling Designing e‐commerce supply chains: a stochastic facility–location approachPagès Bernaus, AdelaRamalhinho-Lourenço, HelenaJuan, Angel A.Calvet Mir, LauraE-commerceSupply chain managementCapacitated facility location problemStochastic combinatorial optimizationSimheuristicsStochastic programmingE‐Commerce activity has been increasing during recent years, and this trend is expected to continue in the near future. e‐Commerce practices are subject to uncertainty conditions and high variability in customers’ demands. Considering these characteristics, we propose two facility–location models that represent alternative distribution policies in e‐commerce (one based on outsourcing and another based on in‐house distribution). These models take into account stochastic demands as well as more than one regular supplier per customer. Two methodologies are then introduced to solve these stochastic versions of the well‐known capacitated facility–location problem. The first is a two‐stage stochastic‐programming approach that uses an exact solver. However, we show that this approach is not appropriate for tackle large‐scale instances due to the computational effort required. Accordingly, we also introduce a “simheuristic” approach that is able to deal with large‐scale instances in short computing times. An extensive set of benchmark instances contribute to illustrate the efficiency of our approach, as well as its potential utility in modern e‐commerce practices.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness and FEDER (TRA2013-48180-C3-P, TRA2015-71883-REDT) and the Erasmus+ programme (2016-1-ES01-KA108-023465). We also thank the support of the UOC doctoral programme.Wiley202020202017info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/44394http://dx.doi.org/10.1111/itor.12433reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésInternational Transactions in Operational Research. 2017 July 7;26(2):507-28info:eu-repo/grantAgreement/ES/1PE/TRA2013-48180-C3-Pinfo:eu-repo/grantAgreement/ES/1PE/TRA2015-71883-REDTThis is the peer reviewed version of the following article: Pagès Bernaus A, Ramalhinho H, Juan AA, Calvet L. Designing e-commerce supply chains: a stochastic facility-location approach. Int Trans Oper Res. 2017 July 7;26(2):507-28, which has been published in final form at http://dx.doi.org/10.1111/itor.12433. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.info:eu-repo/semantics/openAccessoai:repositori.upf.edu:10230/443942026-06-12T07:21:37Z
dc.title.none.fl_str_mv Designing e‐commerce supply chains: a stochastic facility–location approach
title Designing e‐commerce supply chains: a stochastic facility–location approach
spellingShingle Designing e‐commerce supply chains: a stochastic facility–location approach
Pagès Bernaus, Adela
E-commerce
Supply chain management
Capacitated facility location problem
Stochastic combinatorial optimization
Simheuristics
Stochastic programming
title_short Designing e‐commerce supply chains: a stochastic facility–location approach
title_full Designing e‐commerce supply chains: a stochastic facility–location approach
title_fullStr Designing e‐commerce supply chains: a stochastic facility–location approach
title_full_unstemmed Designing e‐commerce supply chains: a stochastic facility–location approach
title_sort Designing e‐commerce supply chains: a stochastic facility–location approach
dc.creator.none.fl_str_mv Pagès Bernaus, Adela
Ramalhinho-Lourenço, Helena
Juan, Angel A.
Calvet Mir, Laura
author Pagès Bernaus, Adela
author_facet Pagès Bernaus, Adela
Ramalhinho-Lourenço, Helena
Juan, Angel A.
Calvet Mir, Laura
author_role author
author2 Ramalhinho-Lourenço, Helena
Juan, Angel A.
Calvet Mir, Laura
author2_role author
author
author
dc.subject.none.fl_str_mv E-commerce
Supply chain management
Capacitated facility location problem
Stochastic combinatorial optimization
Simheuristics
Stochastic programming
topic E-commerce
Supply chain management
Capacitated facility location problem
Stochastic combinatorial optimization
Simheuristics
Stochastic programming
description E‐Commerce activity has been increasing during recent years, and this trend is expected to continue in the near future. e‐Commerce practices are subject to uncertainty conditions and high variability in customers’ demands. Considering these characteristics, we propose two facility–location models that represent alternative distribution policies in e‐commerce (one based on outsourcing and another based on in‐house distribution). These models take into account stochastic demands as well as more than one regular supplier per customer. Two methodologies are then introduced to solve these stochastic versions of the well‐known capacitated facility–location problem. The first is a two‐stage stochastic‐programming approach that uses an exact solver. However, we show that this approach is not appropriate for tackle large‐scale instances due to the computational effort required. Accordingly, we also introduce a “simheuristic” approach that is able to deal with large‐scale instances in short computing times. An extensive set of benchmark instances contribute to illustrate the efficiency of our approach, as well as its potential utility in modern e‐commerce practices.
publishDate 2017
dc.date.none.fl_str_mv 2017
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/44394
http://dx.doi.org/10.1111/itor.12433
url http://hdl.handle.net/10230/44394
http://dx.doi.org/10.1111/itor.12433
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv International Transactions in Operational Research. 2017 July 7;26(2):507-28
info:eu-repo/grantAgreement/ES/1PE/TRA2013-48180-C3-P
info:eu-repo/grantAgreement/ES/1PE/TRA2015-71883-REDT
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv reponame:Repositorio Digital de la UPF
instname:Universitat Pompeu Fabra
instname_str Universitat Pompeu Fabra
reponame_str Repositorio Digital de la UPF
collection Repositorio Digital de la UPF
repository.name.fl_str_mv
repository.mail.fl_str_mv
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