Redes neuronales: Optimización Multiobjetivo de la Estructura de una Silla utilizando un Híbrido de Redes Neuronales Artificiales y NSGA-II

Autores/as

  • A. Alvarado-Iniesta
  • A. Del Valle
  • J. L. García-Alcaraz
  • N. D. Pérez-González

Palabras clave:

Redes Neuronales Artificiales, Optimización Multiobjetivo, NSGA-II, Optimización Estructural

Resumen

Resumen

Se presenta un híbrido de redes neuronales artificiales y NSGA-II para la optimización multiobjetivo del diseño de una silla estándar con respecto a medidas estructurales. Los objetivos a optimizarse son la deformación y peso de la silla. Se realizan simulaciones por computadoras para obtener ambas respuesta de interés. Las variables de diseño se establecen en base a optimización de dimensiones. Redes neuronales artificiales son empleadas para mapear la relación entre las variables de diseño y los variables de salida. Después, NSGA-II es usado para encontrar el conjunto de soluciones óptimas de Pareto. Los resultados muestran que la metodología empleada brinda al diseñador versatilidad y robustez de escoger diferentes escenarios de acuerdo con las necesidades actuales de diseño en términos de estructura de la silla.

Descargas

Citas

Abe A, Kamegawa T, Nakajima Y (2004) Optimization of construction of tire reinforcement by genetic algorithm. Optimization and Engineering 5:77-92.

Asadi E, Gameiro da Silva M, Henggeler- Antunes C, Dias L, Glicksman L (2014) Multi-objective optimization for building retrofit: A model using genetic algorithm and artificial neural network and an application. Energy and Building 81:444-456.

Bahraminasab M, Sahari B, Edwards K, Farahmand F, Hong T, Arumugam M, Jahan A (2014) Multi-objective design optimization of functionally graded material for the femoral component of a total knee replacement. Materials and Design 53:159-173.

Cazacu R, Grama L (2014) Steel truss optimization using genetic algorithms and FEA. Procedia Technology 12:339-346.

Chen W, Zhou X, Wang H, Wang W (2010) Multi-objective optimal approach for injection molding based on surrogate model and particle swarm optimization algorithm. Journal of Shanghai Jiaotong University 15:88- 93.

Cheng J, Liu Z, Tan J (2013) Multiobjective optimization of injection molding parameters based on soft computing and variable complexity method. International Journal of Advanced Manufacturing Technology 66:907- 916.

Christensen P, Klarbring A (2009) An introduction to Structural Optimization. Springer, Canada. Coello C, Christiansen A (2000) Multiobjective optimization of trusses using genetic algorithms. Computers and Structures 75:647-660.

Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective Genetic Algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 6(2):182-197.

Kitayama S, Natsume S (2014) Multi-objective optimization of volume shrinkage and clamping force for plastic injection molding via sequential approximate optimization. Simulation Modelling Practice and Theory 48:35-44.

Lee D, Morillo C, Bugeda G, Oller S, Onate E (2012) Multilayered composite structure design optimization using distributed/parallel multi-objective evolutionary algorithms. Composite Structures 94:1087- 1096.

Magnier L, Haghighat F (2010) Multiobjective optimization of building design using TRNSYS simulations, genetic algorithm, and artificial neural network. Building and Environment 45:739-746.

Morris M, Mitchell T (1995) Exploratory designs for computational experiments, Journal of Statistical Planning and Inference 43:381-402.

Narayanan S, Azarm S (1999) On improving multiobjective genetic algorithms for design optimization. Structural Optimization 18:146-155.

Quaglia C, Yu N, Thrall A, Paolucci S (2014) Balancing energy efficiency and structural performance through multi-objective shape optimization: Case study of a rapidly deployable origami-inspired shelter. Energy and Building 82:733-745.

Rodríguez J, Medaglia A, Casas J (2005) Approximation to the optimum design of a motorcycle frame using finite element analysis and evolutionary algorithms. In: Bass E (ed) Proceedings of the 2005 Systems and Information Engineering Design Symposium. IEEE, Virginia, pp. 277-285.

Serafinska A, Kaliske M, Zopf C, Graf W (2013). A multi-objective optimization approach with consideration of fuzzy variables applied to structural tire design. Computers and Structures 116:7-19.

Stadler W (1986) Multicriteria optimization in mechanics (a survey). Applied Mechanics Reviews 37(2):277-286.

Weigang A, Weiji L (2007) Interactive multi- objective optimization design for the pylon structure of an airplane. Chinese Journal of Aeronautics 20:524-528.

Publicado

2015-10-29

Cómo citar

[1]
A. Alvarado-Iniesta, A. Del Valle, J. L. García-Alcaraz, y N. D. Pérez-González, «Redes neuronales: Optimización Multiobjetivo de la Estructura de una Silla utilizando un Híbrido de Redes Neuronales Artificiales y NSGA-II», Cult. Científ. y Tecnol., n.º 56, oct. 2015.

Número

Sección

Artículos