Lot-splitting and scheduling algorithm of multi-level assembly job shops

被引:0
|
作者
Li Y. [1 ]
Liu J. [1 ]
Chen Q. [1 ]
Mao N. [1 ]
机构
[1] Guangdong Provincial Key Lab of CIM, Guangdong University of Technology, Guangzhou
基金
中国国家自然科学基金;
关键词
Assembly job shops; Genetic algorithms; Hierarchically coupled constraints; Lot splitting and scheduling; Multi-level product structure;
D O I
10.13196/j.cims.2021.08.013
中图分类号
学科分类号
摘要
Is practical extension of job shop, it is oriented to the manufacturing of assembly products with multi-level BOM structure. The products need to go through two stages of parts processing and assembly. The assembly of higher parts can only begin after the complete set of its direct parts, that is, there is a hierarchical coupling constraint between the parts at all levels. Aiming at the difficult coordination of differentiated parts' processing and assembly progress in multi-level assembly job shop, the reasonable batching of parts could improve workshop mobility, achieve more flexible progress coordination and shorten the production cycle. A batch scheduling model for minimizing makespan in such workshops was presented. The batch division strategy in the processing/assembly phase and an improved genetic algorithm based on feasible region search were proposed. The initial population generation, crossover and mutation of this improved genetic algorithm considered the dynamic constraints brought by the batch change, which could always guarantee the legitimacy of chromosomes in the evolutionary process. The basic performance of the proposed algorithm was verified by experiments, the adaptability of different batching strategies to three typical product structures was revealed, and the good effect of collaborative complexity oriented strategy was illustrated. © 2021, Editorial Department of CIMS. All right reserved.
引用
收藏
页码:2307 / 2320
页数:13
相关论文
共 18 条
  • [1] JIN Fenghe, KONG Fansen, JIN Dongyuan, Scheduling rules of assembly job shop based on equipment availability time constraint, Computer Integrated Manufacturing Systems, 14, 9, pp. 1727-1732, (2008)
  • [2] SUN Hu, ZHOU Jingyan, Implementation of immune particle swarm optimization algorithm for assembly job shop scheduling, Journal of Wuhan University of Technology:Information and Management Engineering Edition, 41, 3, pp. 282-286, (2019)
  • [3] LU H L, HUANG G Q, YANG Haidong, Integrating order review/release and dispatching rules for assembly job shop scheduling using a simulation approach, International Journal of Production Research, 49, 3, pp. 647-669, (2011)
  • [4] THURER M, STEVENSON M, SILVA C, Et al., The application of workload control in assembly job shops:An assessment by simulation, International Journal of Production Research, 50, 18, pp. 5048-5062, (2012)
  • [5] ZHAO Shikui, HAN Qing, WANG Guicong, Integrated product scheduling algorithm based on partition coding of virtual parts, Computer Integrated Manufacturing Systems, 21, 9, pp. 2435-2445, (2015)
  • [6] SHI Fei, ZHAO Shikui, Genetic algorithm based on process constraint chain coding is used to solve the problem of integrated product scheduling, China Mechanical Engineering, 28, 20, pp. 2483-2492, (2017)
  • [7] WANG Fuji, ZHAO Guokai, JIA Zhenyuan, Assembly operation scheduling based on feasible domain genetic algorithm, Computer Integrated Manufacturing Systems, 16, 1, pp. 115-120, (2010)
  • [8] ZOU Pan, RAJORA M, LIANG S Y., A new algorithm based on evolutionary computation for hierarchically coupled constraint optimization:methodology and application to assembly job-shop scheduling[J], Journal of Scheduling, 21, 5, pp. 545-563, (2018)
  • [9] WANG Haiyan, WANG Wanliang, HUANG Fengli, Overview of batch optimal scheduling and prospect of energy-saving research, Computer Integrated Manufacturing Systems, 23, 3, pp. 542-556, (2017)
  • [10] WONG T C, NGAN S C., A comparison of hybrid genetic algorithm and hybrid particle swarm optimization to minimize makespan for assembly job shop[J], Applied Soft Computing, 13, 3, pp. 1391-1399, (2013)