Cotton blending optimization based on improved differential evolution algorithm

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.