Modelling customer satisfaction for product development using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@Article{Chan:2009:JED,
  author =       "Kit Yan Chan and C. K. Kwong and T. C. Wong",
  title =        "Modelling customer satisfaction for product
                 development using genetic programming",
  journal =      "Journal of Engineering Design",
  year =         "2011",
  volume =       "22",
  number =       "1",
  pages =        "55--68",
  month =        jan,
  publisher =    "Taylor \& Francis",
  keywords =     "genetic algorithms, genetic programming, SBSE, SPL,
                 interaction terms, higher-order terms, customer
                 satisfaction, design attributes",
  ISSN =         "0954-4828",
  DOI =          "doi:10.1080/09544820902911374",
  abstract =     "Product development involves several processes in
                 which product planning is the first one. Several tasks
                 normally are required to be conducted in the
                 product-planning process and one of them is to
                 determine settings of design attributes for products.
                 Facing with fierce competition in marketplaces,
                 companies try to determine the settings such that the
                 best customer satisfaction of products could be
                 obtained.To achieve this, models that relate customer
                 satisfaction to design attributes need to be developed
                 first. Previous research has adopted various modelling
                 techniques to develop the models, but those models are
                 not able to address interaction terms or higher-order
                 terms in relating customer satisfaction to design
                 attributes, or they are the black-box type models. In
                 this paper, a method based on genetic programming (GP)
                 is presented to generate models for relating customer
                 satisfaction to design attributes. The GP is first used
                 to construct branches of a tree representing structures
                 of a model where interaction terms and higher-order
                 terms can be addressed. Then an orthogonal
                 least-squares algorithm is used to determine the
                 coefficients of the model. The models thus developed
                 are explicit and consist of interaction terms and
                 higher-order terms in relating customer satisfaction to
                 design attributes. A case study of a digital camera
                 design is used to illustrate the proposed method.",
  notes =        "Matlab a Department of Industrial and Systems
                 Engineering, The Hong Kong Polytechnic University,
                 Kowloon, Hong Kong",
}

Genetic Programming entries for Kit Yan Chan Che Kit Kwong T C Wong

Citations