基于改进遗传算法的细纱接头路径指引方法OACSTPCD

In order to improve splicing efficiency of the whole break in spinning workshop,a spun yarn splicing path guidance model with the optimization of the whole workshop breakage splicing path as the objective function was established under the condition of the single spindle monitoring system of yarn responding to the yarn breakage information.And the splicing path models of greedy algorithm,genetic algorithm and improved genetic algorithm were solved by Python programming language respectively.Combined with the traditional tour splicing path and the simulation tests of three algorithms in the efficiency,running speed and quality,the feasibility of the improved genetic algorithm for spun yarn splicing path guidance method was combined and verified.The experimental results showed that the average efficiency of the improved genetic algorithm was increased by 11.8%compared with the traditional tour path.And the solutions were better than the other two algorithms.Compared with genetic algorithm,the response time of improved genetic algorithm was much shorter with an average of 1.25 s,the fluctuation was small,and the time efficiency was increased by 80.3%.It is considered that the improved genetic algorithm was superior to other algorithms in efficiency,running speed and solution quality.It has higher application advantages in the field of spun yarn splicing,which can significantly improve the splicing efficiency and reduce the cost.