| 摘 要: 针对机器故障和紧急订单两种动态事件对印刷包装车间调度方案产生干扰的问题，设计了以最大完工时间、机器负荷、机器总能耗为目标的车间动态调度多目标优化模型。针对灰狼算法种群多样性差、后期收敛速度慢、易陷入局部最优的缺点，提出了一种改进灰狼算法(Improved Gray Wolf Optimization, IGWO)，并进行案例仿真实验。实验结果表明，出现机器故障和紧急订单的情况时，与传统调度方案相比，所提方法分别缩短了2.74%和2.05%的最大完工时间，节省了3.42%和3.04%的机器总能耗，并减少了1.20%和1.24%的机器负荷。 |
| 关键词: 印刷包装车间；动态调度；灰狼算法；多目标优化 |
|
中图分类号: TP278
文献标识码: A
|
|
| Dynamic Scheduling Method of Printing and Packaging Workshop based on Improved Grey Wolf Optimization |
|
PENG Laihu1,2, WAN Lulu1, LI Jianqiang3, YUAN Yanhong1, WANG Weihua1
|
( 1.Zhejiang Sci -Tech University, Hangzhou 310000, China;
2.Research Institute of Zhejiang Sci -Tech University in Longgang, Wenzhou 325000, China;
3.Zhejiang University, Hangzhou 310000, China)
laihup@zstu.edu.cn; luluw27@163.com; wzcnljq@126.com; yyh@zstu.edu.cn; wwhjiushiwo@163.com
|
| Abstract: In order to solve the problem that two dynamic events, machine failure and emergency order, interfere with the scheduling scheme of the printing and packaging workshop, this paper proposes to design a multi-objective optimization model for dynamic scheduling of the workshop with the objectives of maximum completion time, machine load and total machine energy consumption. Aiming at the disadvantages of the Grey Wolf algorithm, such as poor population diversity, slow convergence speed in the later stage, and easy to fall into local optimum, this paper proposes an Improved Grey Wolf Algorithm (IGWO), and case simulation experiments are carried out. The experimental results show that in the case of machine failure and emergency order, compared with the traditional scheduling scheme, the proposed method shortens the maximum completion time by 2.74 % and 2.05 %, saves the total machine energy consumption by 3.42 % and 3.04 %, and reduces the machine load by 1.20 % and 1.24 %, respectively. |
| Keywords: printing and packaging workshop; dynamic scheduling; Grey Wolf algorithm; multi-objective optimization |
