IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i2p342-d1322923.html
   My bibliography  Save this article

Linear Disassembly Line Balancing Problem with Tool Deterioration and Solution by Discrete Migratory Bird Optimizer

Author

Listed:
  • Shujin Qin

    (Research Center of the Economic and Social Development of Henan East Provincial Joint, Shangqiu Normal University, Shangqiu 476000, China
    College of Information and Control Engineering, Liaoning Petrochemical University, Fushun 113001, China)

  • Jiaxin Wang

    (Artificial Intelligence and Software College, Liaoning Petrochemical University, Fushun 113001, China)

  • Jiacun Wang

    (Department of Computer Science and Software Engineering, Monmouth University, West Long Branch, NJ 07764, USA)

  • Xiwang Guo

    (College of Information and Control Engineering, Liaoning Petrochemical University, Fushun 113001, China)

  • Liang Qi

    (College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China)

  • Yaping Fu

    (School of Business, Qingdao University, Qingdao 266071, China)

Abstract

In recent years, the global resource shortage has become a serious issue. Recycling end-of-life (EOL) products is conducive to resource reuse and circular economy and can mitigate the resource shortage issue. The disassembly of EOL products is the first step for resource reuse. Disassembly activities need tools, and tool deterioration occurs inevitably during the disassembly process. This work studies the influence of tool deterioration on disassembly efficiency. A disassembly line balancing model with the goal of maximizing disassembly profits is established, in which tool selection and assignment is a critical part. A modified discrete migratory bird optimizer is proposed to solve optimization problems. The well-known IBM CPLEX optimizer is used to verify the correctness of the model. Six real-world products are used for disassembly experiments. The popular fruit fly optimization algorithm, whale optimization algorithm and salp swarm algorithm are used for search performance comparison. The results show that the discrete migratory bird optimizer outperforms all three other algorithms in all disassembly instances.

Suggested Citation

  • Shujin Qin & Jiaxin Wang & Jiacun Wang & Xiwang Guo & Liang Qi & Yaping Fu, 2024. "Linear Disassembly Line Balancing Problem with Tool Deterioration and Solution by Discrete Migratory Bird Optimizer," Mathematics, MDPI, vol. 12(2), pages 1-21, January.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:2:p:342-:d:1322923
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/2/342/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/2/342/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. McGovern, Seamus M. & Gupta, Surendra M., 2007. "A balancing method and genetic algorithm for disassembly line balancing," European Journal of Operational Research, Elsevier, vol. 179(3), pages 692-708, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Özceylan, Eren & Paksoy, Turan & Bektaş, Tolga, 2014. "Modeling and optimizing the integrated problem of closed-loop supply chain network design and disassembly line balancing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 142-164.
    2. Battaïa, Olga & Dolgui, Alexandre, 2013. "A taxonomy of line balancing problems and their solutionapproaches," International Journal of Production Economics, Elsevier, vol. 142(2), pages 259-277.
    3. Bhattacharya, Sourabh & Govindan, Kannan & Ghosh Dastidar, Surajit & Sharma, Preeti, 2024. "Applications of artificial intelligence in closed-loop supply chains: Systematic literature review and future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    4. Ondemir, Onder & Gupta, Surendra M., 2014. "A multi-criteria decision making model for advanced repair-to-order and disassembly-to-order system," European Journal of Operational Research, Elsevier, vol. 233(2), pages 408-419.
    5. Bingtao Hu & Yixiong Feng & Hao Zheng & Jianrong Tan, 2018. "Sequence Planning for Selective Disassembly Aiming at Reducing Energy Consumption Using a Constraints Relation Graph and Improved Ant Colony Optimization Algorithm," Energies, MDPI, vol. 11(8), pages 1-18, August.
    6. Xuhui Xia & Wei Liu & Zelin Zhang & Lei Wang & Jianhua Cao & Xiang Liu, 2019. "A Balancing Method of Mixed-model Disassembly Line in Random Working Environment," Sustainability, MDPI, vol. 11(8), pages 1-16, April.
    7. Shujin Qin & Xinkai Xie & Jiacun Wang & Xiwang Guo & Liang Qi & Weibiao Cai & Ying Tang & Qurra Tul Ann Talukder, 2024. "An Optimized Advantage Actor-Critic Algorithm for Disassembly Line Balancing Problem Considering Disassembly Tool Degradation," Mathematics, MDPI, vol. 12(6), pages 1-19, March.
    8. Kalaycılar, Eda Göksoy & Azizoğlu, Meral & Yeralan, Sencer, 2016. "A disassembly line balancing problem with fixed number of workstations," European Journal of Operational Research, Elsevier, vol. 249(2), pages 592-604.
    9. D. E. Ighravwe & S. A. Oke & K. A. Adebiyi, 2017. "Preventive maintenance task balancing with spare parts optimisation via big-bang big-crunch algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 811-822, November.
    10. Jianhua Cao & Xuhui Xia & Lei Wang & Zelin Zhang & Xiang Liu, 2019. "A Novel Multi-Efficiency Optimization Method for Disassembly Line Balancing Problem," Sustainability, MDPI, vol. 11(24), pages 1-16, December.
    11. Can B. Kalayci & Olcay Polat & Surendra M. Gupta, 2016. "A hybrid genetic algorithm for sequence-dependent disassembly line balancing problem," Annals of Operations Research, Springer, vol. 242(2), pages 321-354, July.
    12. Fang, Yilin & Liu, Quan & Li, Miqing & Laili, Yuanjun & Pham, Duc Truong, 2019. "Evolutionary many-objective optimization for mixed-model disassembly line balancing with multi-robotic workstations," European Journal of Operational Research, Elsevier, vol. 276(1), pages 160-174.
    13. Abdeljaouad, Mohamed Amine & Bahroun, Zied & Omrane, Anissa & Fondrevelle, Julien, 2015. "Job-shop production scheduling with reverse flows," European Journal of Operational Research, Elsevier, vol. 244(1), pages 117-128.
    14. Wanlin Yang & Zixiang Li & Chenyu Zheng & Zikai Zhang & Liping Zhang & Qiuhua Tang, 2024. "Multi-Objective Optimization for a Partial Disassembly Line Balancing Problem Considering Profit and Carbon Emission," Mathematics, MDPI, vol. 12(8), pages 1-19, April.
    15. Süleyman Mete & Faruk Serin & Zeynel Abidin Çil & Erkan Çelik & Eren Özceylan, 2023. "A comparative analysis of meta-heuristic methods on disassembly line balancing problem with stochastic time," Annals of Operations Research, Springer, vol. 321(1), pages 371-408, February.
    16. Lixia Zhu & Zeqiang Zhang & Yi Wang & Ning Cai, 2020. "On the end-of-life state oriented multi-objective disassembly line balancing problem," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1403-1428, August.
    17. Wei Meng & Xiufen Zhang, 2020. "Optimization of Remanufacturing Disassembly Line Balance Considering Multiple Failures and Material Hazards," Sustainability, MDPI, vol. 12(18), pages 1-16, September.
    18. Ziyan Zhao & Pengkai Xiao & Jiacun Wang & Shixin Liu & Xiwang Guo & Shujin Qin & Ying Tang, 2023. "Improved Brain-Storm Optimizer for Disassembly Line Balancing Problems Considering Hazardous Components and Task Switching Time," Mathematics, MDPI, vol. 12(1), pages 1-19, December.
    19. Hu, Peng & Chu, Feng & Dolgui, Alexandre & Chu, Chengbin & Liu, Ming, 2024. "Integrated multi-product reverse supply chain design and disassembly line balancing under uncertainty," Omega, Elsevier, vol. 126(C).
    20. Ömer Faruk Yılmaz & Büşra Yazıcı, 2022. "Tactical level strategies for multi-objective disassembly line balancing problem with multi-manned stations: an optimization model and solution approaches," Annals of Operations Research, Springer, vol. 319(2), pages 1793-1843, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2024:i:2:p:342-:d:1322923. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.