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Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | Miguel, Fabio Maximiliano | - |
dc.contributor.author | Frutos, Mariano | - |
dc.contributor.author | Méndez, Máximo | - |
dc.contributor.author | Tohmé, Fernando | - |
dc.contributor.author | González, Begoña | - |
dc.date.accessioned | 2024-04-25T14:46:33Z | - |
dc.date.available | 2024-04-25T14:46:33Z | - |
dc.date.issued | 2024-04-19 | - |
dc.identifier.citation | Miguel, F.M.; Frutos, M.; Méndez, M.; Tohmé, F.; González, B. Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System. Mathematics 2024, 12, 1246. https://doi.org/10.3390/math12081246 | es_ES |
dc.identifier.issn | 2227-7390 | es_ES |
dc.identifier.other | https://www.mdpi.com/2227-7390/12/8/1246 | es_ES |
dc.identifier.uri | http://rid.unrn.edu.ar/handle/20.500.12049/11553 | - |
dc.description.abstract | This paper investigates the performance of a two-stage multi-criteria decision-making procedure for order scheduling problems. These problems are represented by a novel nonlinear mixed integer program. Hybridizations of three Multi-Objective Evolutionary Algorithms (MOEAs) based on dominance relations are studied and compared to solve small, medium, and large instances of the joint order batching and picking problem in storage systems with multiple blocks of two and three dimensions. The performance of these methods is compared using a set of well-known metrics and running an extensive battery of simulations based on a methodology widely used in the literature. The main contributions of this paper are (1) the hybridization of MOEAs to deal efficiently with the combination of orders in one or several picking tours, scheduling them for each picker, and (2) a multi-criteria approach to scheduling multiple picking teams for each wave of orders. Based on the experimental results obtained, it can be stated that, in environments with a large number of different items and orders with high variability in volume, the proposed approach can significantly reduce operating costs while allowing the decision-maker to anticipate the positioning of orders in the dispatch area. | es_ES |
dc.format.extent | 1246 | es_ES |
dc.language.iso | en | es_ES |
dc.publisher | MDPI | es_ES |
dc.relation.uri | https://www.mdpi.com/2227-7390/12/8/1246 | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | - |
dc.title | Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System | es_ES |
dc.type | Articulo | es_ES |
dc.rights.license | Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) | - |
dc.description.filiation | Miguel, Fabio Maximiliano. Universidad Nacional de Río Negro. CONICET. Sede Alto Valle y Valle Medio. Río Negro, Argentina | es_ES |
dc.description.filiation | Frutos, Mariano. Universidad Nacional del Sur. Departamento de Ingeniería. IIESS UNS-CONICET. Buenos Aires, Argentina | es_ES |
dc.description.filiation | Méndez, Mariano. Universidad de Las Palmas de Gran Canaria. SIANI. Las Palmas de Gran Canaria, Spain | es_ES |
dc.description.filiation | Tohmé, Fernando. Universidad Nacional del Sur. Departamento de Economía. INMABB UNS-CONICET. Buenos Aires, Argentina | es_ES |
dc.description.filiation | González, Begoña. Universidad de Las Palmas de Gran Canaria. SIANI. Las Palmas de Gran Canaria, Spain | es_ES |
dc.subject.keyword | multiple criteria decision-making | es_ES |
dc.subject.keyword | multi-objective evolutionary algorithms | es_ES |
dc.subject.keyword | order batchingproblem | es_ES |
dc.subject.keyword | order picking problem | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.subject.materia | Matemática Aplicada | es_ES |
dc.subject.materia | Gestión y Administración | es_ES |
dc.subject.materia | Ingenierías, Ciencia y Teconologías (general) | es_ES |
dc.origin.lugarDesarrollo | Sede Alto Valle y Valle Medio, Universidad Nacional de Río Negro | es_ES |
dc.relation.journalissue | 12 | es_ES |
dc.description.review | true | es_ES |
dc.description.resumen | This paper investigates the performance of a two-stage multi-criteria decision-making procedure for order scheduling problems. These problems are represented by a novel nonlinear mixed integer program. Hybridizations of three Multi-Objective Evolutionary Algorithms (MOEAs) based on dominance relations are studied and compared to solve small, medium, and large instances of the joint order batching and picking problem in storage systems with multiple blocks of two and three dimensions. The performance of these methods is compared using a set of well-known metrics and running an extensive battery of simulations based on a methodology widely used in the literature. The main contributions of this paper are (1) the hybridization of MOEAs to deal efficiently with the combination of orders in one or several picking tours, scheduling them for each picker, and (2) a multi-criteria approach to scheduling multiple picking teams for each wave of orders. Based on the experimental results obtained, it can be stated that, in environments with a large number of different items and orders with high variability in volume, the proposed approach can significantly reduce operating costs while allowing the decision-maker to anticipate the positioning of orders in the dispatch area. | es_ES |
dc.relation.journalTitle | Mathematics | es_ES |
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Miguel_F_2024_MOEAS.pdf | Miguel et al. 2024 Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System | 616,44 kB | Adobe PDF | Visualizar/Abrir |
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