A novel optimization approach to minimize aggregate-fit-loss for improved breast sizing

Jie Pei, Jintu Fan, Susan P. Ashdown

    Research output: Journal article publicationJournal articleAcademic researchpeer-review

    12 Citations (Scopus)


    Ready-to-wear clothing is typically based on the body-shape of human fit models that an apparel company hires. The body-shape difference between a consumer and the fit model of their size results in fit-loss of a certain degree. Aggregate-fit-loss is a concept attempting to quantify and estimate the accumulative fit-loss that a population may encounter. This paper reports on a novel method that minimizes the aggregate-fit-loss of a sizing system for bras, through shape categorization and optimized selection of prototypes (which can be regarded as the most appropriate fit models, or standard dress forms) for the categorized groups. A fit-loss function was introduced that calculates the dissimilarity between any two three-dimensional body scans, via pointwise comparisons of the point-to-origin distances of 9000 points on the scan surface. The within-group aggregate-fit-loss is minimized by an algorithm that returns the optimal prototype for the group. The overall aggregate-fit-loss is reduced by breast shape categorization based on the dissimilarities between the scans. Finally, the constraint of band sizes was brought into the categorization to provide a more feasible solution for improved bra sizing. The findings of this study can also contribute to the optimization of sizing systems for other apparel products.

    Original languageEnglish
    Pages (from-to)1823-1836
    Number of pages14
    JournalTextile Research Journal
    Issue number15-16
    Publication statusPublished - 1 Aug 2020


    • aggregate-fit-loss
    • band size
    • bra sizing
    • breast shape
    • optimization
    • three-dimensional body scanning

    ASJC Scopus subject areas

    • Chemical Engineering (miscellaneous)
    • Polymers and Plastics


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