【摘要】 目前传统服装行业与计算机科学技术的结合大多集中于智能服装设计和人体建模等领域，而基于用户喜好的服装定制系统的研究较少。文章运用交互式遗传算法，将人的情感、喜好等基于目标的隐性决策因素纳入系统，以用户评分作为适应度函数，逐步对评价机制进行改善，从而降低系统主观评分机制带来的误差，以获取最优的服装设计方案。实验结果表明：交互式遗传算法在优化服装推荐方案具有较高可行性和实用性，用户可以根据自身的情感喜好，对不同风格款式的服装选择评分，并通过进化计算生成符合用户内心期望的服装设计作品。更多还原

【Abstract】 At present, the traditional clothing industry is closely combined with computer science and technology, and most of them focus on intelligent clothing design and human body modeling, while there are few researches on clothing recommendation based on user preferences. The interactive genetic algorithm is used to incorporate goal-based implicit decision factors such as human emotion and preference into the system, and the user rating is taken as the fitness function to gradually improve the evaluation mechanism, so as to reduce the error caused by the subjective rating mechanism of the system and obtain the optimal fashion design scheme. The experimental results show that interactive genetic algorithm has high feasibility and practicability in the optimization of clothing recommendation scheme. Users can choose and score different styles of clothing according to their emotional preferences, and generate design works in line with users’ inner expectations through evolutionary calculation.更多还原