IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i17p2734-d1469099.html
   My bibliography  Save this article

Unified Modeling and Multi-Objective Optimization for Disassembly Line Balancing with Distinct Station Configurations

Author

Listed:
  • Tao Yin

    (School of Mechanical Engineering, Dongguan University of Technology, Dongguan 523808, China)

  • Yuanzhi Wang

    (School of Mechanical Engineering, Dongguan University of Technology, Dongguan 523808, China)

  • Shixi Cai

    (School of Mechanical Engineering, Dongguan University of Technology, Dongguan 523808, China)

  • Yuxun Zhang

    (School of Mechanical Engineering, Dongguan University of Technology, Dongguan 523808, China)

  • Jianyu Long

    (School of Mechanical Engineering, Dongguan University of Technology, Dongguan 523808, China)

Abstract

Disassembly line balancing (DLB) is a crucial optimization item in the recycling and remanufacturing of waste products. Considering the variations in the number of operators assigned to each station, this study investigates DLBs with six distinct station configurations: single-manned, multi-manned, single-robotic, multi-robotic, single-manned–robotic, and multi-manned–robotic setups. First, a unified mixed-integer programming (MIP) model is established for Type-I DLBs with each configuration to minimize four objectives: the number of stations, the number of operators, the total disassembly time, and the idle balancing index. To obtain more solutions, a novel bi-metric is proposed to replace the quadratic idle balancing index and is used in lexicographic optimization. Subsequently, based on the unified Type-I models, a unified MIP model for Type-II DLBs is established to minimize the cycle time, the number of operators, the total disassembly time, and the idle balancing index. Finally, the correctness of the established unified models and the effectiveness of the proposed bi-metric are verified by solving two disassembly cases of lighters and hairdryers, which further shows that the mathematical integration method of unified modeling has significant theoretical value for the multi-objective optimization of the DLBs with six distinct station configurations.

Suggested Citation

  • Tao Yin & Yuanzhi Wang & Shixi Cai & Yuxun Zhang & Jianyu Long, 2024. "Unified Modeling and Multi-Objective Optimization for Disassembly Line Balancing with Distinct Station Configurations," Mathematics, MDPI, vol. 12(17), pages 1-24, September.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:17:p:2734-:d:1469099
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/17/2734/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/17/2734/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ali Koc & Ihsan Sabuncuoglu & Erdal Erel, 2009. "Two exact formulations for disassembly line balancing problems with task precedence diagram construction using an AND/OR graph," IISE Transactions, Taylor & Francis Journals, vol. 41(10), pages 866-881.
    2. Lixia Zhu & Zeqiang Zhang & Yi Wang, 2018. "A Pareto firefly algorithm for multi-objective disassembly line balancing problems with hazard evaluation," International Journal of Production Research, Taylor & Francis Journals, vol. 56(24), pages 7354-7374, December.
    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. Junkai He & Feng Chu & Feifeng Zheng & Ming Liu, 2021. "A green-oriented bi-objective disassembly line balancing problem with stochastic task processing times," Annals of Operations Research, Springer, vol. 296(1), pages 71-93, January.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Qi Zhang & Yang Xing & Man Yao & Jiacun Wang & Xiwang Guo & Shujin Qin & Liang Qi & Fuguang Huang, 2024. "An Improved Discrete Bat Algorithm for Multi-Objective Partial Parallel Disassembly Line Balancing Problem," Mathematics, MDPI, vol. 12(5), pages 1-22, February.
    7. Yusha Zhou & Xiuping Guo & Dong Li, 2022. "A dynamic programming approach to a multi-objective disassembly line balancing problem," Annals of Operations Research, Springer, vol. 311(2), pages 921-944, April.
    8. Peng Hu & Feng Chu & Yunfei Fang & Peng Wu, 2022. "Novel distribution-free model and method for stochastic disassembly line balancing with limited distributional information," Journal of Combinatorial Optimization, Springer, vol. 43(5), pages 1423-1446, July.
    9. Bentaha, Mohand-Lounes & Voisin, Alexandre & Marangé, Pascale, 2020. "A decision tool for disassembly process planning under end-of-life product quality," International Journal of Production Economics, Elsevier, vol. 219(C), pages 386-401.
    10. Liang, Wei & Zhang, Zeqiang & Yin, Tao & Zhang, Yu & Wu, Tengfei, 2023. "Modelling and optimisation of energy consumption and profit-oriented multi-parallel partial disassembly line balancing problem," International Journal of Production Economics, Elsevier, vol. 262(C).
    11. Battaïa, Olga & Dolgui, Alexandre, 2022. "Hybridizations in line balancing problems: A comprehensive review on new trends and formulations," International Journal of Production Economics, Elsevier, vol. 250(C).
    12. 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.
    13. Bentaha, Mohand Lounes & Battaïa, Olga & Dolgui, Alexandre & Hu, S. Jack, 2015. "Second order conic approximation for disassembly line design with joint probabilistic constraints," European Journal of Operational Research, Elsevier, vol. 247(3), pages 957-967.
    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. 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.
    17. Devika Kannan & Kiran Garg & P. C. Jha & Ali Diabat, 2017. "Integrating disassembly line balancing in the planning of a reverse logistics network from the perspective of a third party provider," Annals of Operations Research, Springer, vol. 253(1), pages 353-376, June.
    18. He, Junkai & Chu, Feng & Dolgui, Alexandre & Anjos, Miguel F., 2024. "Multi-objective disassembly line balancing and related supply chain management problems under uncertainty: Review and future trends," International Journal of Production Economics, Elsevier, vol. 272(C).
    19. Junyong Liang & Shunsheng Guo & Yunfei Zhang & Wenfang Liu & Shengwen Zhou, 2021. "Energy-Efficient Optimization of Two-Sided Disassembly Line Balance Considering Parallel Operation and Uncertain Using Multiobjective Flatworm Algorithm," Sustainability, MDPI, vol. 13(6), pages 1-23, March.
    20. Jin-Ling Bei & Ming-Xin Zhang & Ji-Quan Wang & Hao-Hao Song & Hong-Yu Zhang, 2023. "Improved Hybrid Firefly Algorithm with Probability Attraction Model," Mathematics, MDPI, vol. 11(2), pages 1-59, January.

    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:17:p:2734-:d:1469099. 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.