Instrumental shade sorting of coloured fabrics using genetic algorithm and particle swarm optimisation

Abstract

In the present research by combination of Clemson Colour Clustering (CCC) instrumental shade sorting method and two metaheuristic algorithms, a genetic algorithm (GA) and a particle swarm optimisation (PSO), two new shade sorting methods, called CCCGA and CCCPSO were proposed. Then these proposed methods were applied on 16 well-prepered colour sets made of coloured fabrics and their results were compared using some important performance evaluation factors. The results of the methods were also compared with conventional CCC shade sorting method and a method based on CCC combined with k-means technique (CCCk). The results obtained from various shade sorting methods showed that the CCCGA and CCCPSO methods successfully sorted the coloured fabrics with high efficiency, and their results slightly outperformed the results of the CCC method.