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An optimisation method for complex product design
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DOI：10.1080/17517575.2012.743682.png)
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Abstract
En 中文
Designing a complex product such as an aircraft usually requires both qualitative and quantitative data and reasoning. To assist the design process, a critical issue is how to represent qualitative data and utilise it in the optimisation. In this study, a new method is proposed for the optimal design of complex products: to make the full use of available data, information and knowledge, qualitative reasoning is integrated into the optimisation process. The transformation and fusion of qualitative and qualitative data are achieved via the fuzzy sets theory and a cloud model. To shorten the design process, parallel computing is implemented to solve the formulated optimisation problems. A parallel adaptive hybrid algorithm (PAHA) has been proposed. The performance of the new algorithm has been verified by a comparison with the results from PAHA and two other existing algorithms. Further, PAHA has been applied to determine the shape parameters of an aircraft model for aerodynamic optimisation purpose.
Keywords:
qualitative and quantitative data
parallel computing
heuristic algorithm
genetic algorithm
simulated annealing
aircraft design
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