In the process of fabric spreading, the variance of fabric yardage between fabric rolls may lead to a difference in fabric loss during spreading. As there are numerous combinations the arrangement of the fabric roll sequences for each cutting lay, it is difficult to construct a roll planning to minimise the fabric wastage during spreading in apparel manufacturing. Recent advances in computing technology, especially in the area of computational intelligence, can be used to handle this problem. Among the different computational intelligence techniques, genetic algorithms (GA) are particularly suitable. GAs are probabilistic search methods that employ a search technique based on ideas from natural genetics and evolutionary principles. This paper presents the details of GA and explains how the problem of roll planning can be formulated for GA to solve. The result of the study shows that an optimal roll planning can be worked out by using GA approach. It is possible to save a considerable amount of fabric when the best roll planning is used for the production.
Hui Patrick, C.L., Ng Frency, S.F. and Chan Keith, C.C. (2000), "A study of the roll planning of fabric spreading using genetic algorithms", International Journal of Clothing Science and Technology, Vol. 12 No. 1, pp. 50-62. https://doi.org/10.1108/09556220010313832Download as .RIS
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