Abstract
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.
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