An automatic scheduling method for weaving enterprises based on genetic algorithm

As the multi-varieties and small-batch production mode become more popular in weaving enterprises, the traditional manual operated scheduling exposes the disadvantages of low work efficiency and unsatisfying result. In this paper, by summarizing the weakness previous model, a more practical optimization model is developed for weaving production scheduling to reduce the schedulers’ labor. The model describes the optimization of warp beam looming schedule in weaving process based on the analysis of the schedulers’ working process in weaving enterprises. Genetic algorithm (GA) is adopted to solve the model. To improve the computational efficiency and avoid prematurity convergence of GA, the termination condition is updated and the genetic parameters are optimized based on statistical data. The improved GA with optimized parameters gets solutions superior to manual scheduling with a quicker convergence, which has great practical value.