Scheduling Optimization of Aluminum Extrusion Production Line Based on Timed Petri Net and BSO Algorithm

doi:10.16182/j.issn1004731x.joss.21-0844

Abstract

Abstract:

For the problems of long production period and low efficiency caused by the complicated processes and large scheduling capacity of aluminum extrusion production line in industrial production, a timed Petri net (TdPN) scheduling model of aluminum extrusion production line is proposed and analyzed for reasonableness. The brain storm optimization (BSO) algorithm is introduced into the model, and an optimized scheduling algorithm for aluminum extrusion scheduling problems is proposed based on the individual encoding and decoding methods. The simulated annealing local search mechanism is used to improve the performance of BSO algorithm in the later stage, which can achieve the goal of minimizing the batch completion time. Simulation result shows that the proposed method can shorten the production period, improve the production efficiency, and provide a new solution to the production scheduling problem in aluminum extrusion production.

Key words: Petri net, brain storm optimization(BSO), scheduling, aluminum extrusion production lines, industrial production

CLC Number:

TP391.9

Yali Wu, Shuting He, Yanxi Yang, Lianqiang Feng, Fuqiang Wang, Yulu Chen. Scheduling Optimization of Aluminum Extrusion Production Line Based on Timed Petri Net and BSO Algorithm[J]. Journal of System Simulation, 2023, 35(1): 178-189.

Figures/Tables 11

Fig. 1

Fig. 2

Fig. 3

Table 1

Fig. 4

Fig. 5

Fig. 6

Table 2

Table 3

Fig. 7

Fig. 8

References 20

1	李彦瑞, 杨春节, 张瀚文, 等. 流程工业数字孪生关键技术探讨[J]. 自动化学报, 2021, 47(3): 501-514.
	Li Yanrui, Yang Chunjie, Zhang Hanwen, et al. Discussion on Key Technologies of Digital Twins in Process Industry[J]. Acta Automatica Sinica, 2021, 47(3): 501-514.
2	丁进良, 杨翠娥, 陈远东, 等. 复杂工业过程智能优化决策系统的现状与展望[J]. 自动化学报, 2018, 44(11): 1931-1943.
	Ding Jinliang, Yang Cui'e, Chen Yuandong, et al. Current Status and Prospects of Intelligent Optimization Decision-Making Systems for Complex Industrial Processes[J]. Acta Automatica Sinica, 2018, 44(11): 1931-1943.
3	吴亚丽, 钱富才, 惠鏸. 间歇生产中过程调度的建模与分析[J]. 系统仿真学报, 2008, 20(5): 1146-1150, 1284.
	Wu Yali, Qian Fucai, Hui Liu. Modeling and Analysis of Process Scheduling in Batch Production[J]. Journal of System Simulation, 2008, 20(5): 1146-1150, 1284.
4	潘春荣, 黎良. 基于可重入加工组合设备的建模与调度研究[J]. 系统仿真学报, 2016, 28(4): 772-782.
	Pan Chunrong, Li Liang. Research on Modeling and Scheduling Based on Reentrant Machining Combined Equipment[J]. Journal of System Simulation, 2016, 28(4): 772-782.
5	吴大立, 郑中祥, 尹项根, 等. 基于Petri网和多种群遗传算法的海洋核动力平台电力系统网络重构[J]. 电力自动化设备, 2020, 40(8): 160-168.
	Wu Dali, Zheng Zhongxiang, Yin Xianggen, et al. Power System Network Reconstruction of Marine Nuclear Power Platform Based on Petri Net and Multi-population Genetic Algorithm[J]. Electric Power Automation Equipment, 2020, 40(8): 160-168.
6	Cheng Shi, Zhang Mingming, Ma Lianbo, et al. Brain Storm Optimization Algorithm for Solving Knowledge Spillover Problems[EB/OL]. (2020-06-21)[2021-01-12]..
7	Wu Y, Wang X, Li G, et al. Brain Storm Optimization Algorithm Based on Adaptive Inertial Selection Strategy for the RCPSP"[C]// 2019 Chinese Automation Congress (CAC) ( S2688-0938), Hangzhou, China. 2019: 2610-2615.
8	Alzaqebah Malek, Jawarneh Sana, Alwohaibi Maram, et al. Hybrid Brain Storm Optimization Algorithm and Late Acceptance Hill Climbing to Solve the Flexible Job-Shop Scheduling Problem[J/OL]. [2021-06-28]. .
9	Cheng Jian, Chen Jingjing, Guo Yinan, et al. Adaptive CCR-ELM with Variable-Length Brain Storm Optimization Algorithm for Class-Imbalance Learning[J]. Natural Computing (S1567-7818), 2021, 20(1): 11-22.
10	Wu Y, Wang X, Fu Y, et al. Many-objective Brain Storm Optimization Algorithm[J]. IEEE Access (S2169-3536), 2019, 7: 186572-186586.doi:10.1109/ACCESS.2019.296 0874 .
11	闫世昌, 李文宏, 孙彦良. 基于Petri网与改进A*搜索算法的矿井机车调度优化[J]. 科学技术与工程, 2020, 20(15): 5990-5996.
	Yan Shichang, Li Wenhong, Sun Yanliang. Mine Locomotive Scheduling Optimization Based on Petri Net and Improved A* Search Algorithm[J]. Science Technology and Engineering, 2020, 20(15): 5990-5996.
12	潘春荣, 熊文清. 稳态调度下单臂组合设备时间延迟分析与优化[J]. 控制理论与应用, 2019, 36(10): 1719-1729.
	Pan Chunrong, Xiong Wenqing. Time Delay Analysis and Optimization of Single-arm Combined Equipment Under Steady-State Scheduling[J]. Control Theory and Applications, 2019, 36(10): 1719-1729.
13	刘倩, 杨建平, 王柏琳, 等. 基于"炉-机对应"的炼钢-连铸生产调度问题遗传优化模型[J]. 工程科学学报, 2020, 42(5): 645-653.
	Liu Qian, Yang Jianping, Wang Bailin, et al. A Genetic Optimization Model for Steelmaking-Continuous Casting Production Scheduling Based on "Furnace-Machine Correspondence[J]. Journal of Engineering Science, 2020, 42(5): 645-653.
14	田松龄, 陈东祥, 王太勇, 等. 一种异步蚁群算法求解柔性作业车间调度问题[J]. 天津大学学报(自然科学与工程技术版), 2016, 49(9): 920-928.
	Tian Songling, Chen Dongxiang, Wang Taiyong, et al. An Asynchronous Ant Colony Algorithm for Flexible Job Shop Scheduling Problems[J]. Journal of Tianjin University (Natural Science and Engineering Technology Edition), 2016, 49(9): 920-928.
15	李大成, 罗继亮, 孙莎莎, 等. 基于平行Petri网的制造系统调度与控制一体化方法[J/OL]. 自动化学报[2021-02-22]. .
	Li Dacheng, Luo Jiliang, Sun Shasha, et al. Manufacturing System Scheduling and Control Integrated Method Based on Parallel Petri Nets[J/OL]. Acta Automatic Sinica[2021-02-22]..
16	刘慧霞, 李俊红, 王红梅, 等. 具有不可靠资源柔性制造系统的鲁棒控制器设计[J/OL]. 控制与决策[2021-07-26]. .
	Liu Huixia, Li Junhong, Wang Hongmei, et al. Robust Controller Design for Flexible Manufacturing System with Unreliable Resources[J/OL]. Control and Decision[2021-07-26]. .
17	Shi Y H. Brain Storm Optimization Algorithm[C]// Advances in Swarm Intelligence. Berlin Heidelberg: Springer, 2011: 303-309.
18	Vecchi Mario P, Kirkpatrick Scott. Global Wiring by Simulated Annealing[J]. IEEE Trans. on CAD of Integrated Circuits and Systems (S1937-4151), 1983, 2(4): 215-222.
19	邵良杉, 王振, 李昌明. 基于模拟退火与改进粒子群的矿井通风优化算法[J/OL]. 系统仿真学报[2021-08-15]..
	Shao Liangshan, Wang Zhen, Li Changming. Mineventilation Optimization Algorithm Based on Simulated Annealing and Improved Particle Swarm[J/OL]. Journal of System Simulation[2021-08-15]. .
20	林硕, 陈世佳, 韩忠华. 改进HNN算法求解柔性流水车间排产优化问题[J]. 控制工程, 2019, 26(9): 1667-1674.
	Lin Shuo, Chen Shijia, Han Zhonghua. Improved HNN Algorithm to Solve the Optimization Problem of Flexible Flow Shop Scheduling[J]. Control Engineering, 2019, 26(9): 1667-1674.

P_i	含义	T_i	含义
P₁	上料，铝锭加热开始	T₁	分配加热设备
P₂	铝锭加热	T₂	卸载加热设备
P₃	加热结束，挤压开始	T₃	分配挤压机
P₄	上料，挤压开始	T₄	卸载挤压机
P₅	挤压结束，淬火开始	T₅	分配淬火炉
P₆	淬火加工	T₆	卸载淬火炉
P₇	淬火结束，拉伸开始	T₇	分配拉伸机
P₈	拉伸加工	T₈	卸载拉伸机
P₉	拉伸结束，成品锯开始	T₉	分配成品锯
P₁₀	成品锯加工	T₁₀	卸载成品锯
P₁₁	成品锯结束，定尺台开始	T₁₁	分配定尺台
P₁₂	定尺台加工L	T₁₂	卸载定尺台
P₁₃	定尺台结束，包装开始	T₁₃	分配包装机
P₁₄	包装加工	T₁₄	卸载包装机
P₁₅	包装结束，下料
P₁₆	铝锭加热设备
P₁₇	挤压机
P₁₈	淬火炉
P₁₉	拉伸机
P₂₀	成品锯
P₂₁	定尺台
P₂₂	包装机

序号	主要参数	数值
1	pop	200
2	MaxIt	1 000
3	K	4
4	P₅_a	0.2
5	P₆_b	0.8
6	Tem	100

[1]	Guangqiu Huang, He Wang. Dynamic Risk Assessment of VOCs Cross Regional Flow Based on Petri Nets [J]. Journal of System Simulation, 2023, 35(1): 57-68.
[2]	Yarong Chen, Shuchen Guan, Chengjun Huang, Lixia Zhu, Chou FuhDer. Simulation-Based Adaptive Dynamic Scheduling for Bi-objective Parallel Multi-processor Open Shop [J]. Journal of System Simulation, 2023, 35(1): 69-81.
[3]	Wenzhen Ma, Ziming Zou, Jianhui Li, Qinsi Yu, Jizhou Tong, Jingjing Li. Space Science Satellite Data Processing Framework Research and System Implementation [J]. Journal of System Simulation, 2022, 34(7): 1605-1618.
[4]	Hong Zheng, Zerun Liu, Jianhua Huang, Shihui Qian. Verification of Transaction Ordering Dependence Vulnerability of Smart Contract Based on CPN [J]. Journal of System Simulation, 2022, 34(7): 1629-1638.
[5]	Miao Yu, Manru Li, Yu Zhao. Joint Shift Scheduling Method for Call Center with Mechanism of Delay Information [J]. Journal of System Simulation, 2022, 34(7): 1651-1661.
[6]	Yejian Zhao, Yanhong Wang, Jun Zhang, Hongxia Yu, Zhongda Tian. Application of Improved Q Learning Algorithm in Job Shop Scheduling Problem [J]. Journal of System Simulation, 2022, 34(6): 1247-1258.
[7]	Qiwen Zhang, Bin Zhang. Teaching-Learning-Based Optimization Algorithm for Permutation Flowshop Scheduling [J]. Journal of System Simulation, 2022, 34(5): 1054-1063.
[8]	Yongkui Liu, Ming Zeng, Lin Zhang, Jinwei Guo, Siyang Yuan, Yaoyao Ping. Design and Development of a Simulation System for Scheduling in Cloud Manufacturing Based on Microservice Architecture [J]. Journal of System Simulation, 2022, 34(4): 700-711.
[9]	Naiyang Xue, Dan Ding, Hongmin Wang, Yile Fan, Zhongqian Liu. Idea of Infinitesimal Method-introduced Hybrid TT&C Resources Joint Scheduling [J]. Journal of System Simulation, 2022, 34(4): 826-835.
[10]	Fei Ye, Ziqing Li, Yuanjun Laili. Simulation Optimization on Joint Production and Preventive Maintenance Scheduling for Distributed Job-shop [J]. Journal of System Simulation, 2022, 34(4): 688-699.
[11]	Kaituan Feng, Jie Yuan. Research on Discrete Workshop Task Assignment Based on Improved Water Filling Algorithm [J]. Journal of System Simulation, 2022, 34(4): 768-776.
[12]	Kui Chen, Li Bi, Wenya Wang. Research on Integrated Scheduling of AGV and Machine in Flexible Job Shop [J]. Journal of System Simulation, 2022, 34(3): 461-469.
[13]	Guangqiu Huang, Tiantian Wu. Cause Analysis of VOCs Hazards in Related Areas Based on Object Function Petri Net [J]. Journal of System Simulation, 2022, 34(3): 470-481.
[14]	Xinhang He, Erkang Li, Hongchao Zhang. Research on Optimization of Network Resource Utilization in Static Segment of FlexRay Bus [J]. Journal of System Simulation, 2022, 34(3): 564-572.
[15]	Zi'an Zhao, Hong Zhou, Yingjian Lei. Modeling and Optimization for Manufacturing Cell Scheduling Based on Improved Wolf Pack Algorithm and Simulation [J]. Journal of System Simulation, 2022, 34(2): 201-211.