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An optimisation method for complex product design

  • Ni Li*
  • , Wenqing Yi
  • , Zhuming Bi
  • , Haipeng Kong
  • , Guanghong Gong
  • *Corresponding author for this work
  • Beihang University
  • Indiana University-Purdue University Fort Wayne

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)470-489
Number of pages20
JournalEnterprise Information Systems
Volume7
Issue number4
DOIs
StatePublished - Nov 2013

Keywords

  • aircraft design
  • genetic algorithm
  • heuristic algorithm
  • parallel computing
  • qualitative and quantitative data
  • simulated annealing

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