Dissertation/ Thesis
Genetic algorithm applied to generalized cell formation problems
| Title: | Genetic algorithm applied to generalized cell formation problems |
|---|---|
| Authors: | Vin, Emmanuelle |
| Contributors: | Delchambre, Alain, Ndiaye, Alassane Ballé, RIANE, Fouad, Birattari, Mauro, Dolgui, Alexandre A., Bersini, Hugues, Falkenauer, Emanuel |
| Publisher Information: | Universite Libre de Bruxelles, 2010. |
| Publication Year: | 2010 |
| Subject Terms: | Algorithmes génétiques, 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 themanufacturing industries. In regrouping the production of different parts into clusters,the management of the manufacturing is reduced to manage different smallentities. One of the most important problems in the cellular manufacturing is thedesign of these entities called cells. These cells represent a cluster of machines thatcan be dedicated to the production of one or several parts. The ideal design of acellular 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 completelyinside 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 ofa part between two machines belonging to different cells. The final objective is toreduce this traffic between the cells (called inter-cellular traffic).Different methods exist to produce these cells and dedicated them to parts. Tocreate independent cells, the choice can be done between different ways to produceeach part. Two interdependent problems must be solved:• the allocation of each operation on a machine: each part is defined by one orseveral sequences of operations and each of them can be achieved by a set ofmachines. A final sequence of machines must be chosen to produce each part.• the grouping of each machine in cells producing traffic inside and outside thecells.In function of the solution to the first problem, different clusters will be created tominimise 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 efficiencyof the method is highlighted compared to the methods based on two integrated algorithmsor heuristics. Indeed, to form these cells of machines with the allocationof operations on the machines, the used methods permitting to solve large scaleproblems are generally composed by two nested algorithms. The main one calls thesecondary one to complete the first part of the solution. The application domain goesbeyond the manufacturing industry and can for example be applied to the design ofthe electronic systems as explained in the future research. Doctorat en Sciences de l'ingénieur info:eu-repo/semantics/nonPublished |
| Document Type: | Doctoral thesis |
| File Description: | No full-text files |
| Language: | French |
| Access URL: | http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210160 |
| Accession Number: | edsair.od......2101..820db8cf152a105a9ee6548cc8939f47 |
| Database: | OpenAIRE |
| Description not available. |