Optimal development of textile products using Genetic Algorithms

This paper talks about the design new textile products from technical features proposed by the customer. It is an optimization case where the objective function is to minimize the overall costs subject to restrictions on the technical specifications like the raw material, the stress of the warm and/or the fill of the woven or the minimal or maximal weight per unit of the product. The decision variables are the technical parameters with which the product will be developed such as the yarn specifications, the density of the woven, and the percentile of the finishing substances. First, the mathematical model is presented and then it is applied to the requirements of a technical textile factory. The problem is solved by a genetic algorithm whose initial population is obtained from existing similar products, relaxing the specifications. The population is updated only with the new solutions with better objective function value than the best one of the previous population. One concludes that the problem is a nonlinear mixed integer programming case, that the genetic algorithm is a low computational way to solve it and that the further jobs can apply other meta-heuristics or exact methods to solve the problem.