应用改进遗传算法的自动配棉模型优化与应用  

Optimum and application of automatic cotton blending by improved genetic algorithm

作　　者：宋楚平 李少芹 

机构地区：[1]江苏工程职业技术学院机电工程学院,江苏南通226007

出　　处：《纺织学报》2016年第9期151-155,共5页Journal of Textile Research

基　　金：江苏省高等职业院校国内高级访问学者计划资助项目(2014FX);江苏工程职业技术学院科研计划项目(FYKY/2014/3)

摘　　要：针对配棉工艺具有多约束条件的特点和现有自动配棉的不足,提出将改进的遗传算法应用到线性规划优化求解问题中,通过改进遗传算法的初始种群生成策略、遗传算子和进化收敛条件,将配棉约束条件动态融合到种群进化过程中,在保证配棉约束条件的前提下,兼顾了求解的效率和有效性,以达到对自动配棉进行优化的目的。应用结果显示:用改进遗传算法对配棉模型的求解优于基本遗传算法,且配棉的各项指标值符合生产技术要求,在满足混棉质量的前提下,该方法能指导技术人员对候选棉和库存棉做出更合理的选择,有效降低了配棉成本。Aiming at the characteristics of multi-constraints condition and the deficiency of the existing automatic cotton blending, the improved genetic algorithm is applied to linear programming optimization problem. By improving generation strategy of the initial population, genetic operators and evolutionary convergence condition, constraint conditions of cotton blending will be fused dynamically with the evolution process. The efficiency and effectiveness of the solution are considered in the premise of ensuring the constraint conditions of cotton blending so as to optimize automatic cotton blending. The experimental results show that the solution of the improved genetic algorithm is superior to that of the basic genetic algorithm and all index values of cotton blending are in line with the requirements of production technology. Under the premise of meeting the quality of mixed cotton, the method can guide technicians to make a more reasonable choice for the candidate cotton and stock cotton and the cost of cotton blending can be reduced effectively.

关 键 词：自动配棉 配棉模型 改进遗传算法 多约束条件 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]