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dc.contributor.authorAhmed, Dr. Alim Al Ayubspa
dc.contributor.authorJaenudinspa
dc.contributor.authorWidjaja, Gunawanspa
dc.contributor.authorGrimaldo Guerrero, John Williamspa
dc.contributor.authorkadhim, Mustafa Mohammedspa
dc.contributor.authorKolyazov, Konstantin Alexandrovichspa
dc.date.accessioned2022-04-05T12:47:26Z
dc.date.available2022-04-05T12:47:26Z
dc.date.issued2021
dc.identifier.issn1598-7248spa
dc.identifier.urihttps://hdl.handle.net/11323/9112spa
dc.description.abstractThis research was conducted to study the issue of relief facility location hierarchically by consideration of possible road closure during the crisis conditions, road safety, and arrival time of relief facilities under disaster circumstances. High costs are allocated for facilities deployment in a suitable location to meet the demands of injured people. Therefore, location-allocation of emergency facility should be considered in a way to use them for long-term periods. To this end, the extant research designed a multi-objective optimization model to minimize the pre-disaster costs including costs of facilities deployment and road use, and to minimize the post-disaster costs such as cost transportation innetwork roads. Moreover, the innovative part of the studied model in this research examined the road safety and reduction in time taken to have critical facilities in affected areas. To investigate the functional accuracy of the mathematical model, a numerical example with small dimensions was solved using CPLEX Solver, and required sensitivity analysis was described. As the facility location-allocation is an NP-hard issue, two meta-heuristic algorithms were used to solve numerical representations in real dimensions to examine numerical analyses effectively. Results showed that the dragonfly algorithm had the highest efficiency compared to other developed algorithms. The obtained results can be considered as an efficient managerial tool in management organizations involved in the crisis.eng
dc.format.extent8 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.language.isoeng
dc.rightsAtribución 4.0 Internacional (CC BY 4.0)spa
dc.rights© 2021 KIIEspa
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/spa
dc.titleA multi-objective optimization model for relief facility location in crisis conditionseng
dc.typeArtículo de revistaspa
dc.identifier.urlhttps://doi.org/10.7232/iems.2021.20.4.588spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.doi10.7232/iems.2021.20.4.588spa
dc.identifier.eissn2234-6473spa
dc.identifier.instnameCorporación Universidad de la Costaspa
dc.identifier.reponameREDICUC - Repositorio CUCspa
dc.identifier.repourlhttps://repositorio.cuc.edu.co/spa
dc.publisher.placeSouth Koreaspa
dc.relation.ispartofjournalIndustrial Engineering and Management Systemsspa
dc.relation.referencesAlaswad, S. and Salman, S. (2020), Humanitarian aid and relief distribution (HARD) game, Advances in Engineering Education, 8(2), 22-34.spa
dc.relation.referencesBarber, G., Cote, M., Wetmore, F., and Yerkovich, A. (2020), Decision support tool for enhancing supply chain management in disaster relief operations, 2020 Systems and Information Engineering Design Symposium (SIEDS), Charlottesville, VA, USA, 1-6.spa
dc.relation.referencesGhasemi, P., Khalili-Damghani, K., Hafezalkotob, A., and Raissi, S. (2019), Uncertain multi-objective multicommodity multi-period multi-vehicle locationallocation model for earthquake evacuation planning, Applied Mathematics and Computation, 350, 105-132.spa
dc.relation.referencesGhezavati, V., Soltanzadeh, F., and Hafezalkotob, A. (2015), Optimization of reliability for a hierarchical facility location problem under disaster relief situations by a chance-constrained programming and robust optimization, Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 229(6), 542-555.spa
dc.relation.referencesKaveh, M. and Mesgari, M. S. (2019), Improved biogeography-based optimization using migration process adjustment: An approach for location-allocation of ambulances, Computers & Industrial Engineering, 135, 800-813.spa
dc.relation.referencesKovács, G. and Spens, K. M. (2020), Relief supply chain management for disasters: Humanitarian, aid and emergency logistics, Simulation, 436, Available from: https://doi.org/10.4018/978-1-60960-824-8.spa
dc.relation.referencesMadani, H., Arshadi Khamseh, A., and TavakkoliMoghaddam, R. (2021), Solving a new bi-objective model for relief logistics in a humanitarian supply chain by bi-objective meta-heuristic algorithms, Scientia Iranica, 28(5), 2948-2971, Available from: https://doi.org/ 10.24200/sci.2020.53823.3438.spa
dc.relation.referencesMaharjan, R. and Hanaoka, S. (2020), A credibility-based multi-objective temporary logistics hub locationallocation model for relief supply and distribution under uncertainty, Socio-Economic Planning Sciences, 70, 100727.spa
dc.relation.referencesMauliddina, Y. (2020), The role of supply chain finance in humanitarian aid relief, Master Thesis, Politecnico Di Milano School of Industrial and Information Engineering, p.38.spa
dc.subject.proposalHierarchical facility locationeng
dc.subject.proposalCrisis managementeng
dc.subject.proposalMulti-objective optimization modeleng
dc.subject.proposalMeta-heuristic algorithmeng
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dc.relation.citationendpage595spa
dc.relation.citationstartpage588spa
dc.relation.citationissue4spa
dc.relation.citationvolume20spa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa


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