【摘要】 针对配棉优化问题,提出了一种基于改进微分进化算法的计算机配棉方法。先将配棉问题看作一类约束优化问题,建立数学模型;基于标准微分进化算法,使用罚方法处理多个约束条件,并随着进化过程动态调整算法控制参数,形成求解配棉问题的改进微分进化算法。采用纺织企业实际库存的批棉数据进行实验验证,结果表明,该方法优于人工分类排队法和遗传算法,在满足成纱质量约束的前提下,有效地降低了企业的配棉成本,具有较高的实际应用价值。更多还原

【Abstract】 For optimizing cotton blending,an improved differential evolution algorithm is proposed.Firstly,a math model is established taking cotton blending as a kind of constrained optimization problem.Then the differential evolution algorithm is improved to solve this model,which uses the penalty function to handle multi-constraints,and dynamically adjusts control parameters in the evolution process.Finally,the experiment is carried out to verify the proposed method using the actual raw cotton data from a textile enterprise.The results show that this method is superior to classifying and queuing method and genetic algorithm.Under the premise of satisfying the yarn forming quality restraint,this method effectively reduces cotton blending costs for an enterprise,indicating a higher practical application value.更多还原