Bi-criterion optimisation for configuring an assembly supply chain using Pareto ant colony meta-heuristic

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Show simple item record Moncayo Martínez, Luis A. Recio, Gustavo 2020-09-21T11:14:06Z 2020-09-21T11:14:06Z 2014-01-01
dc.identifier.bibliographicCitation Luis A. Moncayo-Martínez,Gustavo Recio. (2014). Bicriterion optimisation for configuring an assembly supply chain using Pareto ant colony meta-heuristic. Journal of Manufacturing Systems, 33(1), pp. 188-195.
dc.identifier.issn 0278-6125
dc.description.abstract An assembly supply chain (SC) is composed of stages that provide the components, assemble both sub-assemblies and final products, and deliver products to the customer. The activities carried out in each stage could be performed by one or more options, thus the decision-maker must select the set of options that minimises the cost of goods sold (CoGS) and the lead time (LT), simultaneously. In this paper, an ant colony-based algorithm is proposed to generate a set of SC configurations using the concept of Pareto optimality. The pheromones are updated using an equation that is a function of the CoGS and LT. The algorithm is tested using a notebook SC problem, widely used in literature. The results show that the ratio between the size of the Pareto Front computed by the proposed algorithm and the size of the one computed by exhaustive enumeration is 90%. Other metrics regarding error ratio and generational distance are provided as well as the CPU time to measure the performance of the proposed algorithm.
dc.description.sponsorship This work was partially supported by the Spanish Ministerio de Ciencia e Innovación, under the project “Gestión de movilidad eficiente y sostenible, MOVES” with grant reference TIN2011-28336.
dc.language.iso eng
dc.publisher Elsevier
dc.rights Copyright © 2013 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.subject.other Supply chain configuration
dc.subject.other Multi-objective optimisation
dc.subject.other Pareto set
dc.subject.other Ant colony system
dc.title Bi-criterion optimisation for configuring an assembly supply chain using Pareto ant colony meta-heuristic
dc.type article
dc.subject.eciencia Informática
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. TIN2011-28336
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 188
dc.identifier.publicationissue 1
dc.identifier.publicationlastpage 195
dc.identifier.publicationtitle JOURNAL OF MANUFACTURING SYSTEMS
dc.identifier.publicationvolume 33
dc.identifier.uxxi AR/0000014717
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