基于量子遗传算法的成品门幅模型参数优化设计

为了解决热定型中影响成品织物门幅的工艺参数难以定量设计的关键技术难题。提出了将量子遗传算法用于成品门幅模型工艺参数优化设计中。建立优化模型,基于该模型采用量子遗传算法,实现了影响成品门幅的工艺参数精确定量设计。用该方法得到的工艺参数加工弹力布,生产成品的门幅与用户要求指标的偏差小于0.1%,完全满足实际生产要求。同时将量子遗传算法与遗传算法在工艺参数的优化设计中进行比较,得出当迭代种群逐渐增大时,量子遗传算法在工艺参数的优化设计中的优势更加明显。

Proccess Parameters Optimization of the Finished Product Width Model Based on Quantum Genetic Algorithm

In order to solve the key technical problem regarding to the difficulty to design the parameters affecting the finished fabric width quantitatively in heat setting process,this paper puts forward the Quantum Genetic Algorithm(Quantum Genetic Algorithm,QGA) that is used to finish the process parameters optimization design of the product door model.First,we establish the optimization model,and then use quantum genetic algorithm based on this model to realize precise and quantitative design of parameters affecting the finished width.We process the elastic cloth by using the process parameters which are obtained by the method in the paper.The deviation in weight,width between the product,and user required index is less than 0.1%,which can meet the actual production requirements fully.At the same time in the paper we can know that quantum genetic algorithm is better than genetic algorithm in optimum design of process parameters in comparison when the iterative population increase gradually.