Multi-objective optimization of material selection for sustainable products: Artificial neural networks and genetic algorithm approach
Materials & Design (1980-2015)Published 8 June 2008
Changchun Zhou, Guofu Yin, Xiao‐Bing Hu
Citations274
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Abstract
Material properties and selection are very important in product design. To get more sustainable products, not only the technical and economic factors, but also the environmental factors should be considered. To satisfy the requirements, evaluation indicators of materials are presented. Environmental impacts were calculated by the Life Cycle Assessment method (LCA method). An integration of artificial neural networks (ANN) with genetic algorithms (GAs) is proposed to optimize the multi-objectives of material selection. It was validated by an example that the system can select suitable materials to develop sustainable products.
Keywords
Materials ScienceEngineering
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