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Engineering Design of Woven Fabrics Using Non-Traditional Optimization Methods: A Comparative Study

机译:非传统优化方法编织面料的工程设计:比较研究

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This work aims to design woven fabrics with desired quality at optimum manufacturing cost by choice of suitable weaving parameters such as count, crimp and thread spacing of warp and weft yarns. To fulfill this goal, we endeavor to devise search based non-traditional optimization methods such as genetic algorithm, particle swarm optimization and simulated annealing for efficiently finding the appropriate combination of weave parameters. The quick response capability of the non-traditional optimization methods would benefit the fabric manufacturers for efficient determination of the required weaving parameters to produce the engineered fabrics. The experimental validation confirms that the particle swarm optimization is most suitable technique for engineering design of woven fabrics.
机译:这项工作旨在通过选择合适的织造参数,如经纱和纬纱的数量,压接和螺纹间距,以最佳的制造成本设计具有所需质量的编织织物。 为了满足这一目标,我们努力设计基于搜索的非传统优化方法,例如遗传算法,粒子群优化和模拟退火,以有效地找到编织参数的适当组合。 非传统优化方法的快速响应能力将有利于织物制造商,以便有效地确定所需的编织参数以生产工程织物。 实验验证证实,粒子群优化是织物工程设计最合适的技术。

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