The use of evolutionary algorithms to solve practical problems in polymer extrusion
This work aims at selecting the operating conditions and designing screws that optimize the performance of single-screw and co-rotating twin-screw extruders, which are machines widely used by the polymer processing industry. A special MOEA, denoted as Reduced Pareto Set Genetic Algorithm, RPSGAe, is...
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| Formato: | bookPart |
| Idioma: | eng |
| Publicado em: |
2004
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| Texto completo: | http://hdl.handle.net/1822/19571 |
| País: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/19571 |
| Resumo: | This work aims at selecting the operating conditions and designing screws that optimize the performance of single-screw and co-rotating twin-screw extruders, which are machines widely used by the polymer processing industry. A special MOEA, denoted as Reduced Pareto Set Genetic Algorithm, RPSGAe, is presented and used to solve these multiobjective combinatorial problems. Twin screw design is formulated as a Travelling Salesman Problem, TSP, given its discrete nature. Various case studies are analyzed and their validity is discussed, thus demonstrating the potential practical usefulness of this approach. |
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