A design approach and a design tool are presented that are based on human analogical reasoning for providing solutions and are used for the design of formworks for the construction of slabs.. Through a case-based design process, past solutions are compared with the current design case, and a subset of them is retrieved according to a defined similarity measure. In the present work, the retrieval process is performed on the basis of a competitive neural network, which is submitted to unsupervised training by using the existing design solutions. The design case is represented in terms of sets of design parameters and associated fuzzy preferences. In engineering design problems whose solutions could not be adapted in order to meet new requirements, the adaptation process is substituted by another approach that evaluates the retrieved design solutions according to the aggregation of the fuzzy preferences assigned to the current design problem. Therefore, the highly evaluated solutions may be manually adapted and modified by the designer based on both his/her creativity and experience. In engineering domains like structural engineering design, which can not be modelled computationally due to many different underlying disciplines, the designer’s personal capabilities may be augmented by a design tool such as the one presented here that substantially assists decision-making.
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Thanks for your contribution to IPROMS 2006. CBD is an interesting topic for me. In the paper, you use neural networks in the retrieval stage and fuzzy preference for the case representation. Have you thought of using any other techniques for CBD? Why do you choose neuro-fuzzy? Thanks.