Comparative Study of Multi-Objective and Single-Objective Optimisation of Colour Matching for Opaque Products

Jiayuan Qian; Haitao Li; Tianjian Li

doi:10.54097/qge9kr66

Authors

Jiayuan Qian
Haitao Li
Tianjian Li

DOI:

https://doi.org/10.54097/qge9kr66

Keywords:

Opaque products, Color matching of products, multi-objective optimization, Particle swarm algorithm, Layered sequence method.

Abstract

Opaque products usually refer to all types of products with opaque packaging. In order to improve the market competitiveness of opaque products, it is crucial to determine the optimal colour scheme for the products. In this paper, we study the colour matching scheme for opaque products, taking different concentrations of red, yellow and blue dye as the research variables, taking the minimum chromatic aberration, the lowest cost, and the type of dye as the objective function, establishing the mathematical model of the optimal colour matching scheme, adopting the single-objective particle swarm algorithm and multi-objective hierarchical sequential method respectively, and using specific examples to carry out a comparative analysis to check the two methods. The results show that the single-objective method can provide the colour matching scheme with the minimum chromatic aberration from the ideal colour, and the multi-objective method can consider the cost and price of dyes as well as the types of dyes to provide a more scientific colour matching scheme. The computational results also verify the validity of the model and show that the model can provide decision-making and support for colour matching schemes for opaque products.

Downloads

Download data is not yet available.

References

Bhuiyan M A R, Islam A, Ali A, et al. Color and chemical constitution of natural dye henna (Lawsonia inermis L) and its application in the coloration of textiles [J]. Journal of Cleaner Production, 2017, 167: 14-22.

Shoustikov A A, You Y, Thompson M E. Electroluminescence color tuning by dye doping in organic light-emitting diodes[J]. IEEE journal of selected topics in quantum electronics, 1998, 4(1): 3-13.

Li Y, Huang Y, Yang L, et al. Study on color ink diffusion in fabrics and color reproduction of digital inkjet printing[J]. Textile Research Journal, 2022, 92(19-20): 3733-3749.

Marks J, Andalman B, Beardsley P A, et al. Design galleries: A general approach to setting parameters for computer graphics and animation[M]//Seminal Graphics Papers: Pushing the Boundaries, Volume 2. 2023: 73-84.

Pei S,Eiji M,Jialei H, et al. Bioinspired Color Elastomers Combining Structural, Dye, and Background Colors.[J]. ACS applied materials & interfaces,2021.

Jiang P F. Research on computer colour matching theory and algorithm [D]. Zhongyuan University of Technology,2016.

Ruihua Y, Chuang H, Bo P, et al. Color-matching model of digital rotor spinning viscose mélange yarn based on the Kubelka–Munk theory [J]. Textile Research Journal,2022,92(3-4).

Wang L J. Research on blending colour measurement based on CIELAB uniform colour space and clustering algorithm [D]. Zhejiang Sci-tech University,2010.

Mahdi S,Hossein S A. Estimation of dye concentration by using Kubelka-Munk and Allen-Goldfinger reflective models: comparing the performance.[J]. Scientific reports,2023,13(1).

Zhang X, Lin Q. Three-learning strategy particle swarm algorithm for global optimization problems[J]. Information Sciences, 2022, 593: 289-313.

Wang X W, Min Y, Gu X S. Multi-objective particle swarm optimization algorithm based on density clustering. J East China Univ Sci Technol Nat Sci Ed, 2019, 45(3): 449

Xing L,Zhang J,Liang H, et al. Intelligent recognition of dominant colors for Chinese traditional costumes based on a mean shift clustering method [J]. The Journal of The Textile Institute,2018,109(10).