Dissertation/ Thesis
Genetic Algorithm Applied to Generalized Cell Formation Problems / Les algorthmes génétiques appliqués aux problèmes de formation de cellules de production avec routages et processes alternatifs
| Title: | Genetic Algorithm Applied to Generalized Cell Formation Problems / Les algorthmes génétiques appliqués aux problèmes de formation de cellules de production avec routages et processes alternatifs |
|---|---|
| Authors: | Vin, Emmanuelle |
| Contributors: | Riane, Fouad, Birattari, Mauro, Ndiaye, Alasanne Ballé, Dolgui, Alexandre, Bersini, Hugues, Falkenauer, Emanuel, Delchambre, Alain, Ndiaye, Alassane Ballé, RIANE, Fouad, Dolgui, Alexandre A. |
| Publisher Information: | Universite Libre de Bruxelles, 2010. |
| Publication Year: | 2010 |
| Subject Terms: | Algorithmes génétiques, 9. Industry and infrastructure, Cellular Manufacturing, résolution simultanée, genetic algorithm, Industrial engineering -- Data processing, Génie industriel -- Informatique, Alternative Process Plans / algorithm génétique, Genetic algorithms, Cell Formation, Sciences de l'ingénieur, Alternative Routings |
| Description: | The objective of the cellular manufacturing is to simplify the management of the manufacturing industries. In regrouping the production of different parts into clusters, the management of the manufacturing is reduced to manage different small entities. One of the most important problems in the cellular manufacturing is the design of these entities called cells. These cells represent a cluster of machines that can be dedicated to the production of one or several parts. The ideal design of a cellular manufacturing is to make these cells totally independent from one another, i.e. that each part is dedicated to only one cell (i.e. if it can be achieved completely inside this cell). The reality is a little more complex. Once the cells are created, there exists still some traffic between them. This traffic corresponds to a transfer of a part between two machines belonging to different cells. The final objective is to reduce this traffic between the cells (called inter-cellular traffic). Different methods exist to produce these cells and dedicated them to parts. To create independent cells, the choice can be done between different ways to produce each part. Two interdependent problems must be solved: • the allocation of each operation on a machine: each part is defined by one or several sequences of operations and each of them can be achieved by a set of machines. A final sequence of machines must be chosen to produce each part. • the grouping of each machine in cells producing traffic inside and outside the cells. In function of the solution to the first problem, different clusters will be created to minimise the inter-cellular traffic. In this thesis, an original method based on the grouping genetic algorithm (Gga) is proposed to solve simultaneously these two interdependent problems. The efficiency of the method is highlighted compared to the methods based on two integrated algorithms or heuristics. Indeed, to form these cells of machines with the allocation of operations on the machines, the used methods permitting to solve large scale problems are generally composed by two nested algorithms. The main one calls the secondary one to complete the first part of the solution. The application domain goes beyond the manufacturing industry and can for example be applied to the design of the electronic systems as explained in the future research. Doctorat en Sciences de l'ingénieur info:eu-repo/semantics/published |
| Document Type: | Doctoral thesis |
| File Description: | 1 full-text file(s): application/pdf; 2 full-text file(s): application/pdf; application/pdf |
| Access URL: | http://hdl.handle.net/2013/ULB-ETD:oai:ulb.ac.be:ETDULB:ULBetd-02022010-153325 |
| Accession Number: | edsair.dedup.wf.002..c7860bd41d1234d5c52df92f3e8d33ef |
| Database: | OpenAIRE |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://explore.openaire.eu/search/publication?articleId=dedup_wf_002%3A%3Ac7860bd41d1234d5c52df92f3e8d33ef Name: EDS - OpenAIRE (ns324271) Category: fullText Text: View record at OpenAIRE |
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| Header | DbId: edsair DbLabel: OpenAIRE An: edsair.dedup.wf.002..c7860bd41d1234d5c52df92f3e8d33ef RelevancyScore: 685 AccessLevel: 3 PubType: Dissertation/ Thesis PubTypeId: dissertation PreciseRelevancyScore: 685.09619140625 |
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| Items | – Name: Title Label: Title Group: Ti Data: Genetic Algorithm Applied to Generalized Cell Formation Problems / Les algorthmes génétiques appliqués aux problèmes de formation de cellules de production avec routages et processes alternatifs – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Vin%2C+Emmanuelle%22">Vin, Emmanuelle</searchLink> – Name: Author Label: Contributors Group: Au Data: Riane, Fouad<br />Birattari, Mauro<br />Ndiaye, Alasanne Ballé<br />Dolgui, Alexandre<br />Bersini, Hugues<br />Falkenauer, Emanuel<br />Delchambre, Alain<br />Ndiaye, Alassane Ballé<br />RIANE, Fouad<br />Dolgui, Alexandre A. – Name: Publisher Label: Publisher Information Group: PubInfo Data: Universite Libre de Bruxelles, 2010. – Name: DatePubCY Label: Publication Year Group: Date Data: 2010 – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Algorithmes+génétiques%22">Algorithmes génétiques</searchLink><br /><searchLink fieldCode="DE" term="%229%2E+Industry+and+infrastructure%22">9. Industry and infrastructure</searchLink><br /><searchLink fieldCode="DE" term="%22Cellular+Manufacturing%22">Cellular Manufacturing</searchLink><br /><searchLink fieldCode="DE" term="%22résolution+simultanée%22">résolution simultanée</searchLink><br /><searchLink fieldCode="DE" term="%22genetic+algorithm%22">genetic algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22Industrial+engineering+--+Data+processing%22">Industrial engineering -- Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Génie+industriel+--+Informatique%22">Génie industriel -- Informatique</searchLink><br /><searchLink fieldCode="DE" term="%22Alternative+Process+Plans+%2F+algorithm+génétique%22">Alternative Process Plans / algorithm génétique</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Cell+Formation%22">Cell Formation</searchLink><br /><searchLink fieldCode="DE" term="%22Sciences+de+l'ingénieur%22">Sciences de l'ingénieur</searchLink><br /><searchLink fieldCode="DE" term="%22Alternative+Routings%22">Alternative Routings</searchLink> – Name: Abstract Label: Description Group: Ab Data: The objective of the cellular manufacturing is to simplify the management of the manufacturing industries. In regrouping the production of different parts into clusters, the management of the manufacturing is reduced to manage different small entities. One of the most important problems in the cellular manufacturing is the design of these entities called cells. These cells represent a cluster of machines that can be dedicated to the production of one or several parts. The ideal design of a cellular manufacturing is to make these cells totally independent from one another, i.e. that each part is dedicated to only one cell (i.e. if it can be achieved completely inside this cell). The reality is a little more complex. Once the cells are created, there exists still some traffic between them. This traffic corresponds to a transfer of a part between two machines belonging to different cells. The final objective is to reduce this traffic between the cells (called inter-cellular traffic). Different methods exist to produce these cells and dedicated them to parts. To create independent cells, the choice can be done between different ways to produce each part. Two interdependent problems must be solved: • the allocation of each operation on a machine: each part is defined by one or several sequences of operations and each of them can be achieved by a set of machines. A final sequence of machines must be chosen to produce each part. • the grouping of each machine in cells producing traffic inside and outside the cells. In function of the solution to the first problem, different clusters will be created to minimise the inter-cellular traffic. In this thesis, an original method based on the grouping genetic algorithm (Gga) is proposed to solve simultaneously these two interdependent problems. The efficiency of the method is highlighted compared to the methods based on two integrated algorithms or heuristics. Indeed, to form these cells of machines with the allocation of operations on the machines, the used methods permitting to solve large scale problems are generally composed by two nested algorithms. The main one calls the secondary one to complete the first part of the solution. The application domain goes beyond the manufacturing industry and can for example be applied to the design of the electronic systems as explained in the future research.<br />Doctorat en Sciences de l'ingénieur<br />info:eu-repo/semantics/published – Name: TypeDocument Label: Document Type Group: TypDoc Data: Doctoral thesis – Name: Format Label: File Description Group: SrcInfo Data: 1 full-text file(s): application/pdf; 2 full-text file(s): application/pdf; application/pdf – Name: URL Label: Access URL Group: URL Data: <link linkTarget="URL" linkTerm="http://hdl.handle.net/2013/ULB-ETD:oai:ulb.ac.be:ETDULB:ULBetd-02022010-153325" linkWindow="_blank">http://hdl.handle.net/2013/ULB-ETD:oai:ulb.ac.be:ETDULB:ULBetd-02022010-153325</link> – Name: AN Label: Accession Number Group: ID Data: edsair.dedup.wf.002..c7860bd41d1234d5c52df92f3e8d33ef |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsair&AN=edsair.dedup.wf.002..c7860bd41d1234d5c52df92f3e8d33ef |
| RecordInfo | BibRecord: BibEntity: Languages: – Text: Undetermined Subjects: – SubjectFull: Algorithmes génétiques Type: general – SubjectFull: 9. Industry and infrastructure Type: general – SubjectFull: Cellular Manufacturing Type: general – SubjectFull: résolution simultanée Type: general – SubjectFull: genetic algorithm Type: general – SubjectFull: Industrial engineering -- Data processing Type: general – SubjectFull: Génie industriel -- Informatique Type: general – SubjectFull: Alternative Process Plans / algorithm génétique Type: general – SubjectFull: Genetic algorithms Type: general – SubjectFull: Cell Formation Type: general – SubjectFull: Sciences de l'ingénieur Type: general – SubjectFull: Alternative Routings Type: general Titles: – TitleFull: Genetic Algorithm Applied to Generalized Cell Formation Problems / Les algorthmes génétiques appliqués aux problèmes de formation de cellules de production avec routages et processes alternatifs Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Vin, Emmanuelle – PersonEntity: Name: NameFull: Riane, Fouad – PersonEntity: Name: NameFull: Birattari, Mauro – PersonEntity: Name: NameFull: Ndiaye, Alasanne Ballé – PersonEntity: Name: NameFull: Dolgui, Alexandre – PersonEntity: Name: NameFull: Bersini, Hugues – PersonEntity: Name: NameFull: Falkenauer, Emanuel – PersonEntity: Name: NameFull: Delchambre, Alain – PersonEntity: Name: NameFull: Ndiaye, Alassane Ballé – PersonEntity: Name: NameFull: RIANE, Fouad – PersonEntity: Name: NameFull: Dolgui, Alexandre A. IsPartOfRelationships: – BibEntity: Dates: – D: 19 M: 03 Type: published Y: 2010 Identifiers: – Type: issn-locals Value: edsair – Type: issn-locals Value: edsairFT |
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