Wardrobe Furniture Color Design Based on Interactive Genetic Algorithm - Xinyu Ma; Yushu Chen; Qianwei Liang; Jinjing Wang (BioResources, 2024)
With the change in consumption environment and habits, the active feedback from users on online shopping platforms serves as a valuable source of information for analyzing user demand. Color design is an important factor in shaping product style and influencing user's purchase decisions. This study combines the Latent Dirichlet Allocation (LDA) and an interactive genetic algorithm (IGA) to investigate the usability of the interactive genetic color selection method for wardrobe color design. Firstly, the LDA model was employed to cluster online review data to identify customer requirements (CRs), then summarize the perceptual evaluation factors (EFs) of color selection. Subsequently, the color selection information from market examples was used as reference to establish the initial population, and the interactive genetic color design process was completed with CorelDraw. Then, the fuzzy comprehensive evaluation method was employed to evaluate the color scheme generated from IGA. The empirical analysis demonstrated that the interactive genetic color selection method can effectively enhance both efficiency and satisfaction in wardrobe design. This study has substantial implications for both theory and practice in the field of wardrobe design and offers designers novel design concepts and methodologies.