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dc.contributor.author | Tordecilla, Rafael D.![]() |
es_ES |
dc.contributor.author | Juan, Angel A.![]() |
es_ES |
dc.contributor.author | Montoya-Torres, Jairo R.![]() |
es_ES |
dc.contributor.author | Quintero-Araujo, Carlos L.![]() |
es_ES |
dc.contributor.author | Panadero, Javier![]() |
es_ES |
dc.date.accessioned | 2023-11-10T19:05:27Z | |
dc.date.available | 2023-11-10T19:05:27Z | |
dc.date.issued | 2021-01 | es_ES |
dc.identifier.issn | 1569-190X | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/199529 | |
dc.description.abstract | [EN] The design of supply chain networks (SCNs) aims at determining the number, location, and capacity of production facilities, as well as the allocation of markets (customers) and suppliers to one or more of these facilities. This paper reviews the existing literature on the use of simulation optimization methods in the design of resilient SCNs. From this review, we classify some of the many works in the topic according to factors such as their methodology, the approach they use to deal with uncertainty and risk, etc. The paper also identifies several research opportunities, such as the inclusion of multiple criteria (e.g., monetary, environmental, and social dimensions) during the design-optimization process and the convenience of considering hybrid approaches combining metaheuristic algorithms, simulation, and machine learning methods to account for uncertainty and dynamic conditions, respectively. | es_ES |
dc.description.sponsorship | This work has been partially supported by the IoF2020 and the Erasmus+ Programs (2018-1-ES01-KA103-049767). We also acknowledge the support of the doctoral programs at the Universitat Oberta de Catalunya and Universidad de La Sabana (grant INGPhD-12-2020). | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Simulation Modelling Practice and Theory | es_ES |
dc.rights | Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) | es_ES |
dc.subject | Resilient supply chain networks design | es_ES |
dc.subject | Simulation-optimization methods | es_ES |
dc.subject | Uncertainty scenarios | es_ES |
dc.subject | Metaheuristics | es_ES |
dc.subject.classification | ESTADISTICA E INVESTIGACION OPERATIVA | es_ES |
dc.title | Simulation-optimization methods for designing and assessing resilient supply chain networks under uncertainty scenarios: A review | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.simpat.2020.102166 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/UOC// INGPhD-12-2020//Doctoral Programs at the Universitat Oberta de Catalunya and Universidad de La Sabana/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC//2018-1-ES01-KA103-049767/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Politécnica Superior de Alcoy - Escola Politècnica Superior d'Alcoi | es_ES |
dc.description.bibliographicCitation | Tordecilla, RD.; Juan, AA.; Montoya-Torres, JR.; Quintero-Araujo, CL.; Panadero, J. (2021). Simulation-optimization methods for designing and assessing resilient supply chain networks under uncertainty scenarios: A review. Simulation Modelling Practice and Theory. 106:1-23. https://doi.org/10.1016/j.simpat.2020.102166 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.simpat.2020.102166 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 23 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 106 | es_ES |
dc.identifier.pmid | 32837454 | es_ES |
dc.identifier.pmcid | PMC7417904 | es_ES |
dc.relation.pasarela | S\500835 | es_ES |
dc.contributor.funder | European Commission | es_ES |
dc.contributor.funder | Universitat Oberta de Catalunya | es_ES |