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首页> 外文期刊>International journal of production economics >Genetic optimization of fabric utilization in apparel manufacturing
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Genetic optimization of fabric utilization in apparel manufacturing

机译：服装制造中织物利用率的遗传优化

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In apparel manufacturing, cut order planning (COP) plays a significant role in managing the cost of materials as fabric usually occupies more than 50% of the total manufacturing cost. Following the details of retail orders in terms of quantity, size and colour, COP seeks to minimize the total manufacturing costs by developing feasible cutting order plans with respect to material, machine and labour. In this paper, a genetic optimized decision-making model using adaptive evolutionary strategies is proposed to assist the production management of the apparel industry in the decision-making process of COP in which a new encoding method with a shortened binary string is devised. Four sets of real production data were collected to validate the proposed decision support method. The experimental results demonstrate that the proposed method can reduce both the material costs and the production of additional garments while satisfying the time constraints set by the downstream sewing department. Although the total operation time used is longer than that using industrial practice, the great benefits obtained by less fabric cost and extra quantity of garments planned and produced largely outweigh the longer operation time required.
机译：在服装制造中，裁剪订单计划（COP）在管理材料成本方面起着重要作用，因为织物通常占总制造成本的50％以上。根据数量，尺寸和颜色的零售订单详细信息，COP寻求通过针对材料，机器和人工制定可行的切割订单计划来最大程度地降低总制造成本。本文提出了一种基于自适应进化策略的遗传优化决策模型，以协助服装行业的生产管理在COP决策过程中，提出一种新的缩短二进制字符串编码方法。收集了四组实际生产数据以验证所提出的决策支持方法。实验结果表明，所提出的方法可以在满足下游缝纫部门设定的时间限制的同时，减少材料成本和额外服装的生产。尽管使用的总操作时间要比使用工业实践的总时间长，但是通过减少织物成本以及计划和生产的成衣数量增加所获得的巨大收益大大超过了所需的更长操作时间。

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