基于多目标遗传算法的热定型工艺参数优化设计  

Proccess Parameters Optimization of Heat Setting Process Based on Multi-Objective Genetic Algorithm

作　　者：周丽春[1] 郜琳琳[1] 金福江[1] 

机构地区：[1]华侨大学信息科学与工程学院,福建厦门361021

出　　处：《江南大学学报（自然科学版）》2012年第4期453-457,共5页Joural of Jiangnan University (Natural Science Edition)　

基　　金：国家自然科学基金项目(60113005);福建省产学研重大项目(2011H6019);弹力棉织物热定型工艺计算机辅助设计系统研究与应用项目(2011G8)

摘　　要：为了解决染整后整理中热定型工艺参数难以定量设计的关键技术难题,将工艺参数优化设计问题视为以成品门幅、克重与客户要求的相应值的绝对误差最小为目标函数,温度、车速、超喂率和上机门幅为优化变量,以根据实际情况中各优化变量的取值范围为约束条件的多目标优化问题。建立多目标优化模型,并基于该模型采用多目标遗传算法,实现了热定型参数精确定量设计。用该方法得到的工艺参数加工弹力布,生产成品的克重、门幅与用户要求指标的偏差小于1%,完全可以满足实际生产要求。In order to solve the key technical problem that it is difficult to quantitatively design the heat setting process parameter in dyeing and finishing, the objective function is established in this paper based on the minimum absolute error of width, weight between the finished product and customer requirements. Taking the temperature, speed, feeding rate and the width as optimization variables, the multi-objective optimization model is established. Then, the design of precise quantitative parameter in heat setting process is realized by using multi-objective genetic algorithm based on the above-mentioned model. The elastic fabric processing with the process parameters from the method mentioned in the paper, which the deviation between the product and user requirements parameters about weight, width is less than 1%, can meet the actual production requirements fully. When the elastic fabric is produced by using the designed parameters with the proposed method for heat-setting process, the deviation between the weight and width of finished product and customer requirements is less than 1%. It can meet the actual production requirements fully.

关 键 词：染整后整理 热定型工艺 多目标遗传算法 参数优化 

分 类 号：TS115.1[轻工技术与工程—纺织材料与纺织品设计]