Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    A guided search genetic algorithm using mined rules for optimal affective product design

    198736_198736.pdf (854.2Kb)
    Access Status
    Open access
    Authors
    Fung, K.Y.
    Kwong, C.
    Chan, Kit Yan
    Jiang, H.
    Date
    2014
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Fung, K.Y. and Kwong, C.K. and Chan, Kit Yan and Jiang, H. 2014. A guided search genetic algorithm using mined rules for optimal affective product design. Engineering Optimization. 46 (8): pp. 1094-1108.
    Source Title
    Engineering Optimization
    DOI
    10.1080/0305215X.2013.823196
    ISSN
    0305215X
    Remarks

    This is an Author's Accepted Manuscript of an article published in Engineering Optimization, 2014, copyright Taylor & Francis, available online at: <a href="http://www.tandfonline.com/10.1080/0305215X.2013.823196">http://www.tandfonline.com/10.1080/0305215X.2013.823196</a>

    URI
    http://hdl.handle.net/20.500.11937/15382
    Collection
    • Curtin Research Publications
    Abstract

    Affective design is an important aspect of new product development, especially for consumer products, to achieve a competitive edge in the marketplace. It can help companies to develop new products that can better satisfy the emotional needs of customers. However, product designers usually encounter difficulties in determining the optimal settings of the design attributes for affective design. In this article, a novel guided search genetic algorithm (GA) approach is proposed to determine the optimal design attribute settings for affective design. The optimization model formulated based on the proposed approach applied constraints and guided search operators, which were formulated based on mined rules, to guide the GA search and to achieve desirable solutions. A case study on the affective design of mobile phones was conducted to illustrate the proposed approach and validate its effectiveness. Validation tests were conducted, and the results show that the guided search GA approach outperforms the GA approach without the guided search strategy in terms of GA convergence and computational time. In addition, the guided search optimization model is capable of improving GA to generate good solutions for affective design.

    Related items

    Showing items related by title, author, creator and subject.

    • Computational Intelligence Techniques for New Product Design
      Chan, Kit Yan; Kwong, C.; Dillon, Tharam S. (2012)
      Applying computational intelligence for product design is a fast-growing and promising research area in computer sciences and industrial engineering. However, there is currently a lack of books, which discuss this research ...
    • A Preliminary Study on Optimizing Injection Moulding Process by Using Response Surface Method
      Sokkalingam, Rajalingam (2009)
      In the injection moulding, the process parameters setting have crucial effects on the quality of products. Obtaining optimal conditions is necessary because the present day competitive conditions force injection moulding ...
    • A study of agribusiness supply chain systems for small farmers in dryland areas of Lombok Island Indonesia : a pluralistic approach
      Tanaya, I Gusti Lanang Parta (2010)
      Despite the contribution that agriculture makes to the Indonesian Gross Domestic Product, the income of small subsistence farmers continues to fall. While many development activities and policies have been implemented to ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.