Optimizing the multi-level location-assignment problem in queue networks using a multi-objective optimization approach

dc.creatorSyah, Rahmad
dc.creatorElveny, Marischa
dc.creatorSoerjati, Enni
dc.creatorGrimaldo Guerrero, John William
dc.creatorRead Jowad, Rawya
dc.creatorSuksatan, Wanich
dc.creatorAravindhan, Surendar
dc.creatorYuryevna Voronkova, Olga
dc.creatorMavaluru, Dinesh
dc.date2022-08-04T14:25:14Z
dc.date2022-08-04T14:25:14Z
dc.date2022
dc.date.accessioned2023-10-03T19:01:36Z
dc.date.available2023-10-03T19:01:36Z
dc.identifierSyah,R.,Elveny,M.,Soerjati,E.,Guerrero,J.,Jowad,R.,Suksatan,W.,Aravindhan,S.,Voronkova,O. & Mavaluru,D.(2022).Optimizing the Multi-Level Location-Assignment Problem in Queue Networks Using a Multi-Objective Optimization Approach. Foundations of Computing and Decision Sciences,47(2) 177-192. https://doi.org/10.2478/fcds-2022-0010
dc.identifier0867-6356
dc.identifierhttps://hdl.handle.net/11323/9430
dc.identifierhttps://doi.org/10.2478/fcds-2022-0010
dc.identifier10.2478/fcds-2022-0010
dc.identifier2300-3405
dc.identifierCorporación Universidad de la Costa
dc.identifierREDICUC - Repositorio CUC
dc.identifierhttps://repositorio.cuc.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9166867
dc.descriptionUsing hubs in distribution networks is an efficient approach. In this paper, a model for the location-allocation problem is designed within the framework of the queuing network in which services have several levels, and customers must go through these levels to complete the service. The purpose of the model is to locate an appropriate number of facilities among potential locations and allocate customers. The model is presented as a multi-objective nonlinear mixed-integer programming model. The objective functions include the summation of the customer and the waiting time in the system and the waiting time in the system and minimizing the maximum possibility of unemployment in the facility. To solve the model, the technique of accurate solution of the epsilon constraint method is used for multi-objective optimization, and Pareto solutions of the problem will be calculated. Moreover, the sensitivity analysis of the problem is performed, and the results demonstrate sensitivity to customer demand rate. Based on the results obtained, it can be concluded that the proposed model is able to greatly summate the customer and the waiting time in the system and reduce the maximum probability of unemployment at several levels of all facilities. The model can also be further developed by choosing vehicles for each customer.
dc.format16 páginas
dc.formatapplication/pdf
dc.formatapplication/pdf
dc.languageeng
dc.publisherWalter de Gruyter GmbH
dc.publisherGermany
dc.relationFoundations of Computing and Decision Sciences
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dc.rights© 2022 Rahmad Syah et al., published by Sciendo This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
dc.rightsAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.sourcehttps://sciendo.com/es/article/10.2478/fcds-2022-0010
dc.subjectHub
dc.subjectReinforced epsilon constraint method
dc.subjectMultilevel services
dc.subjectQueue theory
dc.subjectMulti-objective optimization
dc.subjectLocation-assignment
dc.titleOptimizing the multi-level location-assignment problem in queue networks using a multi-objective optimization approach
dc.typeArtículo de revista
dc.typehttp://purl.org/coar/resource_type/c_6501
dc.typeText
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typehttp://purl.org/redcol/resource_type/ART
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typehttp://purl.org/coar/version/c_ab4af688f83e57aa


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