Journal of Textile Science and Technology

Journal of Textile Science and Technology

3D Garment Design Using Interactive Genetic Algorithm and k-Means Clustering

Document Type : Research/ Original/ Regular Article

Authors
tahere zare zade
Pedram Payvandy
textile department
Abstract
Today, with increasing development and utilization of digital technologies to promote and accelerate artistic
production trends, the use of computers has found a special place in fashion design. In this study, a 3D garment
design system using interactive genetic algorithms and k-means clustering is proposed. Components
of a swimsuit (top style, waist and bottom style) were individually designed using the 3D garment design
software. The fabric designs were reviewed and selected by users to make a database of favorites. The designs
were generated using genetic algorithms on a dummy. By rotation of the dummy, the users could see
all parts of the swimsuit intuitively. In order to reduce the eye strain/fatigue, the total population was limited
into 8 clusters using k-means clustering. Then, the fitness of the designs was determined by the user and the
next generations were produced by this fitness and evolution principles. The results of evolutions indicate the
system efficiency in fashion set design using a fabric pattern set at minimum cost and shortest time according
to user’s satisfaction.
Keywords
3D garment designing
user fatigue
interactive genetic algorithm
k-means method

Subjects

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  • Receive Date 15 January 2016
  • Revise Date 14 February 2016
  • Accept Date 15 March 2016