dc.creatorPedro Pérez Villanueva
dc.creatorElias Gabriel Carrum Siller
dc.date2009
dc.date.accessioned2023-07-20T18:56:57Z
dc.date.available2023-07-20T18:56:57Z
dc.identifierhttp://comimsa.repositorioinstitucional.mx/jspui/handle/1022/396
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7721162
dc.descriptionThis paper presents a hybrid simulation based on multi-objective algorithm for creation and optimization of manufacturing cells; these cells are created by using the principle of group technology with binary matrices. The algorithm used in this paper is the NSGA-II using a seed made by a modified ART neural network, the NSGA-II algorithm is used to maximize the final inventory, minimize the WIP, and minimize the movement time in order to create an optimized cells, after that, the best solution is compared using simulation against the original matrices, the cell formation given by and modify ART neural network and the NSGA-II algorithm without the seed. The solution given by the hybrid NSGA-II algorithm gives superiors solutions when the seed is used.
dc.formatapplication/pdf
dc.languageeng
dc.relationcitation:A Hybrid Simulation Based on Multi-Objective Algorithm for Manufacturing Cells Optimization Carrum-Siller Elías, Torres-Treviño Luis, Pérez-Villanueva Pedro
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.subjectinfo:eu-repo/classification/ARTÍCULO/HYBRID SYSTEMS
dc.subjectinfo:eu-repo/classification/cti/7
dc.subjectinfo:eu-repo/classification/cti/7
dc.titleA Hybrid Simulation Based on Multi-Objective Algorithm for Manufacturing Cells Optimization
dc.typeinfo:eu-repo/semantics/bookPart
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.audiencestudents
dc.audienceresearchers


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