Abstract
AbstractProduct customization is a means that effectively caters to personal needs, and as such, has increasingly caught the attention of both consumers and manufacturers. With technological advancements, the customization of products is now being made available through mobile applications. However, mobile apps need to be easy to use and operate, which presents some challenges for mobile app designers. In response, this study proposes an interactive evolutionary design method for mobile apps, based on an interactive genetic algorithm, to help consumers generate high-quality designs and enhance their retail experience by optimizing synthetic fitness and reducing the user’s fatigue from evaluation. Firstly, a human–computer interaction model for mobile interactive evolutionary design was launched to solve the screen space problem and simplify the evaluation process. Secondly, to accelerate the convergence of the algorithm, this paper combines hesitation patterns to obtain accurate individual fitness. Thirdly, an ongoing prediction and replacement mechanism were presented to improve user experience. After addressing these items, the proposed method is applied to a customization system that involves traditional brocade patterns of the Zhuang ethnic group in southwestern China and validated using a conventional interactive evolutionary design system with an interactive genetic algorithm. The experimental results show that the proposed method increases the designs’ efficiency, and can help consumers effectively customize their product purchases on mobile devices.
Funder
Graduate Research and Innovation Projects of Jiangsu Province
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,General Computer Science
Cited by
2 articles.
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