A fuzzy genetic algorithm for creative shape design
Zhang, Jinglan, Pham, Binh L., & Chen, Yi-Ping Pheobe (2001) A fuzzy genetic algorithm for creative shape design. In The Australian Journal of Intelligent Information Processing Systems, Wuhan, China, pp. 315-329.
Design is a multi-criteria decision-making process under multiple constraints. In the conceptual design stage, design is intrinsically imprecise because of designers’ vague thinking and incomplete initial information. When exploring possible design candidates, designers are generally more interested in sets of the most promising solutions rather than the best single solution. Therefore, in contrast to conventional optimisation approaches that aim to find exact optimal points, we aim to find optimal set of alternatives with variable satisfaction degrees. A fuzzy-set-based approach for representation and optimisation of design objects is particularly suitable for solving this problem. The concept of a fuzzy shape is defined as a family of shapes with similar properties where a fuzzy solid shape is represented by a set of parameters that have fuzzy set values. Evolutionary computation is used to obtain fuzzy solutions to the fuzzy shape optimisation problem since it is the most powerful tool for supporting creative design through multiple objectives, multi-dimensional searching. The representation of fuzzy sets, its initialisation, crossover, mutation, and validation, the ranking approach for fuzzy shapes, and the propagation method of fuzzy information are discussed. A case study for illustrating this fuzzy design approach is provided.
Impact and interest:
Citation countsare sourced monthly fromand citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Conference Paper|
|Additional Information:||For more information, please contact the author.|
|Keywords:||Fuzzy shape, fuzzy shape evolution, fuzzy genetic algorithm, imprecise design|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Neural Evolutionary and Fuzzy Computation (080108)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2002 (please consult author)|
|Deposited On:||26 Oct 2004|
|Last Modified:||02 Feb 2012 19:44|
Repository Staff Only: item control page