Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A study of the roll planning of fabric spreading using genetic algorithms

A study of the roll planning of fabric spreading using genetic algorithms 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Clothing Science and Technology Emerald Publishing

A study of the roll planning of fabric spreading using genetic algorithms

Loading next page...
 
/lp/emerald-publishing/a-study-of-the-roll-planning-of-fabric-spreading-using-genetic-0vs8DQL60T
Publisher
Emerald Publishing
Copyright
Copyright © 2000 MCB UP Ltd. All rights reserved.
ISSN
0955-6222
DOI
10.1108/09556220010313832
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

International Journal of Clothing Science and TechnologyEmerald Publishing

Published: Mar 1, 2000

Keywords: Fabric; Garments; Manufacturing

References