Spinning workshop collaborative scheduling method based on simulated annealing genetic algorithm

被引：0
|
作者：
Zheng X. [1 ]
Bao J. [1 ]
Ma Q. [1 ]
Zhou H. [1 ]
Zhang L. [1 ]
机构：
[1] College of Mechanical Engineering, Donghua University, Shanghai
来源：
Fangzhi Xuebao/Journal of Textile Research | 2020年 / 41卷 / 06期
关键词：
Automated guided vehicle; Collaborative scheduling; Multi-objective optimization; Simulated annealing genetic algorithm; Spinning workshop;
D O I：
10.13475/j.fzxb.20181107906
中图分类号：
学科分类号：
摘要：
In order to solve the multi-objective scheduling problem of automated guided vehicle(AGV) spinning workshop collaborative scheduling system, under the four constraints of technology, processing equipment resources, AGV resources, and batch processing, an AGV spinning workshop collaborative scheduling system model that meets the minimum completion time and maximizes equipment utilization was established. Then, based on the shortcomings of simulated annealing and genetic algorithm, such as low efficiency and easy to fall into local optimal solution, a spinning scheduling system based on simulated annealing genetic algorithm was proposed. The results show that when the number of cotton drums is 50, the scheduling scheme based on simulated annealing genetic algorithm is reduced by 1 162 s and 1 619 s respectively than the simulated annealing and genetic algorithm in the same environment. The utilization rate of equipment and AGV in the yarn workshop has also increased by nearly 12% and 11% respectively. This method has application value in improving the operation efficiency of the ring spinning workshop. Copyright No content may be reproduced or abridged without authorization.
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页码：36 / 41
页数：5
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