The application of intelligent optimization methods injects new vitality into personalized clothing design and effectively improves the efficiency of combining creativity and craftsmanship. In this study, the interactive genetic algorithm is used to optimize the process of personalized clothing design, and the method to enhance the efficiency of combining creativity and craftsmanship is explored. Considering the garment as a whole as a chromosome, the key elements are binary coded, and a single-point crossover mutation is used to continuously optimize the design scheme. The system realizes human-computer collaborative design through the user’s subjective evaluation as an adaptation function, effectively overcoming the limitations of traditional design methods. The experiment selects 8 groups of initial populations, sets the crossover probability 0.6 and mutation probability 0.8, and invites 20 users to participate in the test. The results show that the interactive genetic algorithm can obtain higher aesthetics values compared with the traditional method, with an average improvement rate of 18.32% (comparing with the traditional genetic algorithm) and 35.06% (comparing with the two-dimensional crop method). The average fitness values for users to obtain satisfactory design solutions are all greater than 88.67, and the highest fitness value can reach 97. All users can obtain satisfactory results within 4-8 generations, and the average evolution reaches the maximum value of evaluation in the 9th generation, which is significantly better than that of the traditional genetic algorithm in 12 generations. The experiment proves that the method not only improves the efficiency of personalized clothing design, but also enhances the user’s cognition of the system, realizes the efficient combination of creativity and craftsmanship, and provides a new idea for personalized clothing customization.
