Abstract
At present, the development of our society is still marked by the need for lighter and stronger structures with a minimum manufacturing cost. The materials that are responding best to these needs are composite materials and as a result, these are replacing many traditional materials such as steel, wood or aluminium. Designing composite materials is difficult because it involves designing the geometry of the element and composition. Traditionally, due to the limited knowledge of these materials, these design tasks have been based on approximate methods; the possibilities for creating composite materials is almost unlimited, characterization by testing is very expensive and it is difficult to apply the results to other contexts. Due to this fact, the whole design task relies on the ability of an expert to select the best combination based on their knowledge and experience. This paper presents and compares a genetic Algorithm to design industrial materials.
Keywords
- Genetic Algorithm
- Composite Material
- Crossover Operator
- Simulated Annealing Algorithm
- Stopping Criterion
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Tenorio, E., Gómez-Ruiz, J., Peláez, J.I., Doña, J.M. (2010). A Genetic Algorithm to Design Industrial Materials. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15393-8_50
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DOI: https://doi.org/10.1007/978-3-642-15393-8_50
Publisher Name: Springer, Berlin, Heidelberg
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