Application of improved hybrid genetic algorithm on automatic cotton-blending

Attempting to solve the problems of computer automatic cotton-blending under multi-constrained conditions,the relationship between raw cotton and yarn quality was studied.The advantages and weaknesses of the basic genetic algorithm in solving this problem was analyzed,then a new computer automatic cotton-blending model was designed.It proposes an improved hybrid genetic algorithm by using key techniques such as group ordering and local optimalizing methods.And computer automatic cotton-blending experiments are carried out by using the basic genetic algorithms and the improved hybrid genetic algorithm respectively.The results show that the cotton assorting scheme obtained by the improved hybrid genetic algorithm is more reasonable and the resulting mixed cotton exhibits better quality.The general optimization and convergence speed of the algorithm has been strengthened by adding the local optimization operator and the steepest descent factor at the same time.