METAHEURISTIC-BASED FUZZY C-MEANS ALGORITHM FOR APPAREL SIZING SYSTEM
Sizing system is essential for apparel design and production. Accurate size of apparel is related to customer satisfaction and manufacturing. Several researches had been proposed to create sizing system. This study aims to develop a new sizing system for anthropometry data using novel data mining ap...
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| Main Authors: | , |
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| Format: | Theses and Dissertations NonPeerReviewed |
| Published: |
[Yogyakarta] : Universitas Gadjah Mada
2014
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| Subjects: | |
| Online Access: | https://repository.ugm.ac.id/133758/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=74566 |
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| Institution: | Universitas Gadjah Mada |
| Summary: | Sizing system is essential for apparel design and production. Accurate size
of apparel is related to customer satisfaction and manufacturing. Several
researches had been proposed to create sizing system. This study aims to develop
a new sizing system for anthropometry data using novel data mining approach.
This study employs metaheuristic-based clustering techniques to determine a new
standard sizing system for apparel industry. Through measuring anthropometry of
912 objects (598 males and 304 females) aged between 18 and 25, this study
proposes a sizing system for Indonesian adult with seven variables, hip width, arm
length, waist width, bust width, back-waist length, back-rest width, and stature.
There are two stages for the proposed method. The first stage employs principal
component analysis (PCA) for feature extraction. Then, several metaheuristicbased
techniques will be employed to find the best sizing system which fit to the
population and hybridized with fuzzy c-means. The computational result indicated
that five groups of size are feasible for the current data. In addition, based on the
aggregate loss the proposed model has a good accuracy and the result can be used
as a size recommendation to specify the right size for the customers. |
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