Under the circumstance of perceptual consumption, it is still challenging to grasp consumer's emotions and demands due to the large search space, diversified preferences, and easy fatigue of consumers. To reduce user fatigue and enlarge search space, a novel method was presented to design and optimize the pattern of yarn-dyed plaid fabric using the isolation niche genetic algorithm and rough set theory. Each pattern was encoded as a chromosome based on the real number code. The population was initialized and evolved using INGA to maintain the diversity. The rough set theory was adopted as the fitness function of isolation niche genetic algorithm to extract the consumer's demands. After multiple evolutions, a large set of practical patterns of the yarn-dyed plaid fabric are obtained. Experiments were carried out by 24 testers of different ages and genders. The results prove that the proposed method based on the isolation niche genetic algorithm and rough set theory is feasible and effective, supplying references to the designer.

中文翻译：

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基于隔离生态位遗传算法和粗糙集理论的色织格子织物花型设计与优化

在感性消费的情况下，由于搜索空间大、偏好多样化、消费者容易疲劳，把握消费者的情绪和需求仍然具有挑战性。为了减少用户疲劳，扩大搜索空间，提出了一种利用隔离生态位遗传算法和粗糙集理论设计和优化色织格子织物图案的新方法。每个模式都被编码为基于实数代码的染色体。使用 INGA 对种群进行初始化和进化以保持多样性。采用粗糙集理论作为隔离生态位遗传算法的适应度函数来提取消费者的需求。经过多次演变，得到了大量实用的色织格子布花型。实验由 24 名不同年龄和性别的测试人员进行。结果证明所提出的基于隔离生态位遗传算法和粗糙集理论的方法是可行和有效的，为设计者提供参考。