Parallel disassembly sequence planning for complex products based on genetic algorithm

被引:0
|
作者
Zhang, Xiufen [1 ]
Yu, Gang [2 ]
Wang, Lei [1 ]
Sa, Rina [1 ]
机构
[1] The College of Mechanical Engineer, Inner Mongolia University of Technology, Hohhot,010051, China
[2] The Inner Mongolia Technical College of Mechanics and Electrics, Hohhot,010070, China
关键词
Chromosomes;
D O I
暂无
中图分类号
R318.08 [生物材料学]; Q [生物科学];
学科分类号
07 ; 0710 ; 0805 ; 080501 ; 080502 ; 09 ;
摘要
In order to solve the parallel disassembly sequence planning (PDSP) problem efficiently, a method based on genetic algorithm was developed. According to the uncertain characteristics of disassembly sequence length and the number of parts removed at each step for the PDSP, a chromosome coding method for parallel sequence was presented to express the disassembly sequence and disassembly steps simultaneously. The disassembly hybrid graph (DHG) was constructed to describe the mating contact and disassembly priority relationships among constituting components of the product. From the DHG, the disassembly constraint matrix and adjacent matrix can be deduced so that the chromosome population with a feasibility constraint was generated randomly in order to reduce the search space. The chromosome fitness function combines the total disassembly time and the penalty factor for unfeasible disassembly sequences. Based on the fitness function, the crossover and mutation operation were performed to get the optimum sequence. Finally, an example illustrates the proposed method. ©, 2015, Institute of Computing Technology. All right reserved.
引用
收藏
页码:1327 / 1333
相关论文
共 50 条
  • [11] Product cooperative disassembly sequence and task planning based on genetic algorithm
    Tian, Yongting
    Zhang, Xiufen
    Liu, Zehua
    Jiang, Xingyue
    Xue, Junfang
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2019, 105 (5-6): : 2103 - 2120
  • [12] Product cooperative disassembly sequence and task planning based on genetic algorithm
    Yongting Tian
    Xiufen Zhang
    Zehua Liu
    Xingyue Jiang
    Junfang Xue
    The International Journal of Advanced Manufacturing Technology, 2019, 105 : 2103 - 2120
  • [13] Object selective disassembly sequence planning for complex mechanical products
    Zhang X.
    Zhang S.
    Yi G.
    Lou X.
    Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2010, 46 (11): : 172 - 178
  • [14] Parallel disassembly sequence planning using improved ant colony algorithm
    Yufei Xing
    Dongmei Wu
    Ligang Qu
    The International Journal of Advanced Manufacturing Technology, 2021, 113 : 2327 - 2342
  • [15] Parallel disassembly sequence planning using improved ant colony algorithm
    Xing, Yufei
    Wu, Dongmei
    Qu, Ligang
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2021, 113 (7-8): : 2327 - 2342
  • [16] Disassembly Sequence Planning of Used Smartphone Based on Dual-population Genetic Algorithm
    Yin F.
    Du Z.
    Li L.
    Liang Z.
    An R.
    Wang R.
    Liu G.
    Li, Lin (ll@qust.edu.cn), 1600, Chinese Mechanical Engineering Society (57): : 226 - 235
  • [17] Backtracking Algorithm-based Disassembly Sequence Planning
    Li, Bingbing
    Ding, Li
    Rajai, Mark
    Hu, Di
    Zheng, Shengzi
    25TH CIRP LIFE CYCLE ENGINEERING (LCE) CONFERENCE, 2018, 69 : 932 - 937
  • [18] Asynchronous parallel disassembly sequence planning method of complex products using discrete multi-objective optimization
    Qiu, Lemiao
    Dong, Liangyu
    Wang, Zili
    Zhang, Shuyou
    Xu, Pengcheng
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 2022, 236 (11) : 1466 - 1482
  • [19] Using genetic/simulated annealing algorithm to solve disassembly sequence planning
    Wu Hao & Zuo Hongfu Coll.of Civil Aviation
    Journal of Systems Engineering and Electronics, 2009, 20 (04) : 906 - 912
  • [20] Using genetic/simulated annealing algorithm to solve disassembly sequence planning
    Wu Hao
    Zuo Hongfu
    JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2009, 20 (04) : 906 - 912