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dc.rights.licenceAtribución-NoComercial-SinDerivadas 4.0 Internacional*
dc.contributor.advisorNait Abdallah, Mohamed Rabiespa
dc.contributor.authorBotero Amaya, Mariospa
dc.contributor.authorRodas Herrera, Diego Andrésspa
dc.contributor.authorGelvez Gelvez, Theo Nicolásspa
dc.date.accessioned2021-08-25T16:27:49Z
dc.date.available2021-08-25T16:27:49Z
dc.date.created2021
dc.identifier.urihttp://hdl.handle.net/10554/56625
dc.description.abstractThe aim of this paper is to present a simheuristic approach that obtains robust solutions for a multi-objective hybrid flow shop problem under uncertain processing and release times. This approach minimizes the expected tardiness and standard deviation of tardiness, as a robustness measure for the stated problem. The simheuristic algorithm hybridizes the NSGA-II with a Monte Carlo Simulation process. Initially, the deterministic scenario was tested on 32 different created small size instances and 32 medium and large benchmarked instances. As a result, the proposed algorithm improved quality of solutions by 1.21% against the MILP model and it also performed better than ERD, NEHedd, and ENS2, while consuming a reasonable computational time. Afterwards, one experimental design was carried out using 10 random instances from the same benchmark as a blocking factor, where four factors of interest were considered. The factors and their respective values are number of generations (50, 100), crossover probability (0.8, 0.9), mutation probability (0.1, 0.2), and population size (60, 100). Results show that the factors instance, mutation probability and number of generations, as well as other interactions between them, have a significant effect in the total tardiness for the deterministic scenario, proving the importance of an appropriate selection of parameters when using genetic algorithms to obtain quality solutions. Then, the performance of the proposed NSGA-II was compared against ERD, NEHedd, and ENS2 methods. Results show that our algorithm improves the quality of the solutions for both objective functions, proving the robustness of our solutions for the HFS problem. Finally, two additional generalized experiments were carried out to analyze the effect of number of jobs (10, 20), number of stages (2, 3), shop condition (0.2, 0.6), probability distribution (uniform, lognormal), and CV (0.05, 0.25, 0.4) on both objective functions. The shop condition, probability distribution and CV were proven to be highly influential on the variability of the results, with the only exception being the coefficient of variation having no statistically significant effect on the total tardiness.spa
dc.formatPDFspa
dc.format.mimetypeapplication/pdfspa
dc.language.isospaspa
dc.publisherPontificia Universidad Javerianaspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectNSGA-II
dc.subjectHFS
dc.subjectparámetros inciertos
dc.subjecttiempos de procesamiento
dc.subjecttiempos de liberación
dc.subjectsemi-heurística
dc.titleA robust flexible flow shop problem under processing and release times uncertaintyspa
dc.type.hasversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.title.englishA robust flexible flow shop problem under processing and release times uncertaintyspa
dc.subject.keywordNSGA-II
dc.subject.keywordHFS
dc.subject.keyworduncertain parameters
dc.subject.keywordprocessing times
dc.subject.keywordrelease times
dc.subject.keywordsimheuristic approach
dc.description.abstractenglishThe aim of this paper is to present a simheuristic approach that obtains robust solutions for a multi-objective hybrid flow shop problem under uncertain processing and release times. This approach minimizes the expected tardiness and standard deviation of tardiness, as a robustness measure for the stated problem. The simheuristic algorithm hybridizes the NSGA-II with a Monte Carlo Simulation process. Initially, the deterministic scenario was tested on 32 different created small size instances and 32 medium and large benchmarked instances. As a result, the proposed algorithm improved quality of solutions by 1.21% against the MILP model and it also performed better than ERD, NEHedd, and ENS2, while consuming a reasonable computational time. Afterwards, one experimental design was carried out using 10 random instances from the same benchmark as a blocking factor, where four factors of interest were considered. The factors and their respective values are number of generations (50, 100), crossover probability (0.8, 0.9), mutation probability (0.1, 0.2), and population size (60, 100). Results show that the factors instance, mutation probability and number of generations, as well as other interactions between them, have a significant effect in the total tardiness for the deterministic scenario, proving the importance of an appropriate selection of parameters when using genetic algorithms to obtain quality solutions. Then, the performance of the proposed NSGA-II was compared against ERD, NEHedd, and ENS2 methods. Results show that our algorithm improves the quality of the solutions for both objective functions, proving the robustness of our solutions for the HFS problem. Finally, two additional generalized experiments were carried out to analyze the effect of number of jobs (10, 20), number of stages (2, 3), shop condition (0.2, 0.6), probability distribution (uniform, lognormal), and CV (0.05, 0.25, 0.4) on both objective functions. The shop condition, probability distribution and CV were proven to be highly influential on the variability of the results, with the only exception being the coefficient of variation having no statistically significant effect on the total tardiness.spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.publisher.programIngeniería Industrialspa
dc.publisher.facultyFacultad de Ingenieríaspa
dc.type.localTesis/Trabajo de grado - Monografía - Pregradospa
dc.subject.armarcIngeniería industrial - Tesis y disertaciones académicasspa
dc.subject.armarcAlgoritmos heurísticosspa
dc.subject.armarcHeurísticaspa
dc.subject.armarcMejoramiento de procesosspa
dc.description.degreenameIngeniero (a) Industrialspa
dc.description.degreelevelPregradospa
dc.identifier.instnameinstname:Pontificia Universidad Javerianaspa
dc.identifier.reponamereponame:Repositorio Institucional - Pontificia Universidad Javerianaspa
dc.identifier.repourlrepourl:https://repository.javeriana.edu.cospa
dc.type.coarhttp://purl.org/coar/resource_type/c_7a1f
dc.rights.localDe acuerdo con la naturaleza del uso concedido, la presente licencia parcial se otorga a título gratuito por el máximo tiempo legal colombiano, con el propósito de que en dicho lapso mi (nuestra) obra sea explotada en las condiciones aquí estipuladas y para los fines indicados, respetando siempre la titularidad de los derechos patrimoniales y morales correspondientes, de acuerdo con los usos honrados, de manera proporcional y justificada a la finalidad perseguida, sin ánimo de lucro ni de comercialización. De manera complementaria, garantizo (garantizamos) en mi (nuestra) calidad de estudiante (s) y por ende autor (es) exclusivo (s), que la Tesis o Trabajo de Grado en cuestión, es producto de mi (nuestra) plena autoría, de mi (nuestro) esfuerzo personal intelectual, como consecuencia de mi (nuestra) creación original particular y, por tanto, soy (somos) el (los) único (s) titular (es) de la misma. Además, aseguro (aseguramos) que no contiene citas, ni transcripciones de otras obras protegidas, por fuera de los límites autorizados por la ley, según los usos honrados, y en proporción a los fines previstos; ni tampoco contempla declaraciones difamatorias contra terceros; respetando el derecho a la imagen, intimidad, buen nombre y demás derechos constitucionales. Adicionalmente, manifiesto (manifestamos) que no se incluyeron expresiones contrarias al orden público ni a las buenas costumbres. En consecuencia, la responsabilidad directa en la elaboración, presentación, investigación y, en general, contenidos de la Tesis o Trabajo de Grado es de mí (nuestro) competencia exclusiva, eximiendo de toda responsabilidad a la Pontifica Universidad Javeriana por tales aspectos. Sin perjuicio de los usos y atribuciones otorgadas en virtud de este documento, continuaré (continuaremos) conservando los correspondientes derechos patrimoniales sin modificación o restricción alguna, puesto que, de acuerdo con la legislación colombiana aplicable, el presente es un acuerdo jurídico que en ningún caso conlleva la enajenación de los derechos patrimoniales derivados del régimen del Derecho de Autor. De conformidad con lo establecido en el artículo 30 de la Ley 23 de 1982 y el artículo 11 de la Decisión Andina 351 de 1993, "Los derechos morales sobre el trabajo son propiedad de los autores", los cuales son irrenunciables, imprescriptibles, inembargables e inalienables. En consecuencia, la Pontificia Universidad Javeriana está en la obligación de RESPETARLOS Y HACERLOS RESPETAR, para lo cual tomará las medidas correspondientes para garantizar su observancia.spa
dc.type.driverinfo:eu-repo/semantics/bachelorThesis


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